Intersect helps researchers increase their impact through expert people, a vibrant member community and innovative technologies. Our services are targeted at enhancing capability (skills) through training and capacity (resources) of organisations, disciplines and research groups through an embedded team of experts.
Intersect provides an extensive range of technology-focused training to researchers and higher degree research (HDR) students across Australia including training courses at the awareness, introductory, and intermediate to advanced levels, covering the breadth of research-relevant digital tools and technologies. The training is delivered by Intersect’s team of experts.
Human brains are extremely good at evaluating a small amount of information simultaneously, ignoring anomalies and coming up with an answer to a problem without much in the way of conscious thought. Computers on the other hand are extremely good at performing individual calculations, one at a...
Keywords: Programming
Web scraping is a technique for extracting information from websites. This can be done manually but it is usually faster, more efficient and less error-prone if it can be automated.
Web scraping allows you to convert non-tabular or poorly structured data into a usable, structured format, such as...
Keywords: Data Management, Python
This hands-on training is designed to familiarise you with the data analysis environment of the R programming. In this session, we will traverse into the realm of inferential statistics, beginning with correlation and reliability. We will present a brief conceptual overview and the R procedures...
Keywords: Programming, R
This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in...
Keywords: Data Analysis, SPSS
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
This workshop is an introduction to data structures (DataFrames using...
Keywords: Programming, Python
Course Materials
You'll learn:
- Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries
- Configuring plot elements within seaborn and matplotlib
- Exploring different types of plots using seaborn
Prerequisites:
Either [Learn to...
Keywords: Programming, Python
R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.
But getting started with R can be challenging,...
Keywords: Programming, R
You have written, compiled and run functioning programs in C and/or Fortran. You know how HPC works and you've submitted batch jobs.
Now you want to move from writing single-threaded programs into the parallel programming paradigm, so you can truly harness the full power of High Performance...
Keywords: Research Computing, HPC
Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you.
This course will introduce you to REDCap, a rapidly evolving web tool developed by...
Keywords: Data Management, REDCap
Do you have messy data from multiple inconsistent sources, or open-responses to questionnaires? Do you want to improve the quality of your data by refining it and using the power of the internet?
Open Refine is the perfect partner to Excel. It is a powerful, free tool for exploring, normalising...
Keywords: Data Analysis, Open Refine
A relational database is an extremely efficient, fast and widespread means of storing structured data, and Structured Query Language (SQL) is the standard means for reading from and writing to databases. Databases use multiple tables, linked by well-defined relationships, to store large amounts...
Keywords: Data Management, SQL
Is your computer's limited power throttling your research ambitions? Are your analysis scripts pushing your laptop's processor to its limits? Is your software crashing because you’ve run out of memory? Would you like to unleash to power of the Unix command line to automate and run your analysis...
Keywords: Research Computing, HPC
Julia is a high-level, high-performance dynamic programming language with more than 4,000 external libraries available. Julia allows you to range from tight low-level loops and conditionals, up to a high-level programming style, with its performance approaching and often matching the performance...
Keywords: Programming, Julia
R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.
This half-day course covers one and two-way Analyses of Variance (ANOVA) and their...
Keywords: Programming, R
Have you ever wanted to extract phone numbers out of a block of unstructured text? Or email addresses. Or find all the words that start with “e” and end with “ed”, no matter their length? Or search through DNA sequences for a pattern? Or extract coordinates from GPS data?
Regular Expressions...
Keywords: Data Analysis, Regular Expressions
Most of you would have heard of Cloud and High Performance Computing (HPC), or you may already be using it. HPC is not the same as cloud computing. Both technologies differ in a number of ways, and have some similarities as well.
We may refer to both types as “large scale computing” - but what...
Keywords: Research Computing
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, Python
In all fields of research we are being confronted with a deluge of data; data that needs cleaning and transformation to be used in further analysis. This webinar demonstrates the effective use of programming tools for an initial analysis of COVID-19 datasets, with examples using both R and...
Keywords: Programming, Python, R
Now more than ever researchers are needing to embrace electronic data capture methods to keep their research moving in the midst of social distancing restrictions and decreased access to survey participants. Using a research specific survey tool can not only solve this problem, but also set your...
Keywords: Data Management, REDCap, Qualtrics
Is your computer's limited power throttling your research ambitions? Are your analysis scripts pushing your laptop's processor to its limits? Is your software crashing because you’ve run out of memory? Would you like to unleash to power of the Unix command line to automate and run your analysis...
Keywords: Research Computing, HPC
MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you're just getting started - with MATLAB and, more generally, with programming?
Nothing beats a hands-on, face-to-face training session to get you past the inevitable syntax errors!
So...
Keywords: Programming, MATLAB
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
We teach using Jupyter notebooks, which allow program code, results,...
Keywords: Programming, Python
Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this webinar, we are...
Keywords: Programming, Python, R, MATLAB, Julia
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, Python
Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise,...
Keywords: Data Analysis, Excel
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, R
Julia is a high-level, high-performance dynamic programming language with more than 4,000 external libraries available. Julia allows you to range from tight low-level loops and conditionals, up to a high-level programming style, with its performance approaching and often matching the performance...
Keywords: Programming, Julia
After cleaning your database, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested...
Keywords: Data Analysis, Excel
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
In this workshop, you will explore DataFrames in depth (using the...
Keywords: Programming, Python
Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics?
Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow...
Keywords: Data Management, Qualtrics
Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers.
NVivo allows researchers to simply...
Keywords: Data Management, NVivo
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, R
Would you like to use regular expressions with the classic command line utilities find, grep, sed and awk? These venerable Unix utilities allow you to search, filter and transform large amounts of text (including many common data formats) efficiently and repeatably.
You'll learn:
- find to...
Keywords: Data Analysis, Regular Expressions
R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.
This workshop is an introduction to data...
Keywords: Programming, R
Are you drowning in research data? Do you want to know where you should be storing your data? Are you required to comply with funding body data management requirements, but don't know how?
This workshop is ideal for researchers who want to know how research data management can support project...
Keywords: Data Management, Data Management
R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.
In this workshop, you will learn how to manipulate, explore and get insights from...
Keywords: Programming, R
R has become a popular programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.
The primary goal of this workshop is to familiarise you with basic statistical concepts in R from...
Keywords: Programming, R
R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment.
But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory...
Keywords: Programming, R
This hands-on training is designed to familiarize you further with the SPSS data analysis environment. In this session, we will traverse into the realm of inferential statistics, beginning with linear correlation and reliability. We will present a brief conceptual overview and the SPSS procedures...
Keywords: Data Analysis, SPSS
R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.
In this workshop, you will explore different types of graphs and learn how to...
Keywords: Programming, R
Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers.
NVivo allows researchers to simply...
Keywords: Data Analysis, NVivo
We rarely receive the research data in an appropriate form. Often data is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors.
This webinar targets beginners and presents a quick demonstration of using the most widespread data wrangling tool,...
Keywords: Data Analysis, Excel
Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data.
In this workshop, you will explore DataFrames in depth (using the...
Keywords: Programming, Python
REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with...
Keywords: Data Management, REDCap
This hands-on training is designed to familiarize you further with the SPSS data analysis environment. In this session, we will traverse into the realm of inferential statistics, beginning with linear correlation and reliability. We will present a brief conceptual overview and the SPSS procedures...
Keywords: Data Analysis, SPSS
The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of...
Keywords: Research Computing, Unix
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, Python
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore...
Keywords: Programming, R
Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there...
Keywords: Data Management, Git
R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.
In this workshop, you will learn how to manipulate, explore and get insights from...
Keywords: Programming, R
Tableau is a powerful data visualisation software that can help anyone see and understand their data. With the features to connect to almost any database, drag and drop to create visualizations, and share with a click, it definately makes thing easier.
This course is suitable for all researchers...
Keywords: Data Analysis, Tableau
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Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online
8 August 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-unsw-online-293fa804-95b8-4537-b871-c8c3e44ce959 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-08-08 09:30:00 UTC 2023-08-08 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at UNSW Online
19 July 2023
Data Visualisation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-unsw-online-78c7c702-ec13-48fd-b278-3ca17824c4ae Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-19 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at UNSW Online
15 - 16 August 2023
Excel for Researchers at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-unsw-online-e5d43780-fe1a-4ff2-a72e-8c9f38de2148 Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-08-15 13:30:00 UTC 2023-08-16 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: Python at ACU Online
18 - 19 July 2023
Learn to Program: Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-acu-online-46a479f8-02c1-4918-a968-a3d876c6e001 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: Python at UC Online
7 - 8 June 2023
Learn to Program: Python at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-uc-online-9a9ededa-39cb-49e8-882d-4200f70c194f Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-06-07 13:30:00 UTC 2023-06-08 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UC Online
20 July 2023
Surveying with Qualtrics at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-uc-online-eccd3958-481d-4aef-a64f-5735428578e9 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-20 09:30:00 UTC 2023-07-20 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Longitudinal Trials with REDCap at La Trobe Online
11 July 2023
Longitudinal Trials with REDCap at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/longitudinal-trials-with-redcap-at-la-trobe-online-31fd5a0c-ff05-445a-a73b-ecfd7304d6d4 REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with very little configuration. This course will introduce some of REDCap's more advanced features for running longitudinal studies, and builds on the foundational material taught in REDCAP101 - Managing Data Capture and Surveys with REDCap. #### You'll learn: - Build a longitudinal project - Manage participants throughout multiple events - Configure and use Automated Survey Invitations - Use Smart Variables to add powerful features to your logic - Take advantage of high-granularity permissions for your collaborators - Understand the data structure of a longitudinal project #### Prerequisites: This course requires the participant to have a fairly good basic knowledge of REDCap. To come up to speed, consider taking our [Data Capture and Surveys with REDCap](https://intersect.org.au/training/course/redcap101/) workshop. **For more information, please click [here](https://intersect.org.au/training/course/redcap201).** 2023-07-11 10:00:00 UTC 2023-07-11 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at Western Sydney: Online
7 July 2023
Data Capture and Surveys with REDCap at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-western-sydney-online-43694e10-9009-4267-a477-1d48c300d43d Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-07-07 09:30:00 UTC 2023-07-07 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in Python at UNSW Online
18 July 2023
Data Manipulation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-unsw-online-23fa1a76-a874-43a9-a2ca-11c32e78c95d Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-18 13:30:00 UTC 2023-07-18 16:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
R for Social Scientists at UNSW Online
19 - 20 September 2023
R for Social Scientists at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/r-for-social-scientists-at-unsw-online-915fe503-e24a-44ce-ba66-016a62560e0b R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Data Carpentry. #### You'll learn: - Basic syntax and data types in R - RStudio interface - How to import CSV files into R - The structure of data frames - A brief introduction to data wrangling and data transformation - How to calculate summary statistics - A brief introduction to visualise data #### Prerequisites: No prior experience with programming needed to attend this course. **For more information, please click [here](https://intersect.org.au/training/course/r103).** 2023-09-19 13:30:00 UTC 2023-09-20 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in Python at UC Online
20 June 2023
Data Manipulation in Python at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-uc-online Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-06-20 09:30:00 UTC 2023-06-20 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Getting started with NVivo for Windows at La Trobe Online
25 July 2023
Getting started with NVivo for Windows at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online-1b36cbe0-b606-4ea9-af1a-2baec562ea93 Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2023-07-25 10:00:00 UTC 2023-07-25 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online
10 - 11 August 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-western-sydney-online-898158a8-78fa-4fd5-99f3-04c90abf3ce4 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-08-10 09:30:00 UTC 2023-08-11 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
R for Social Scientists at UNSW Online
6 - 7 June 2023
R for Social Scientists at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/r-for-social-scientists-at-unsw-online-2454c6fa-e47a-4c65-8152-187f3e405389 R is quickly gaining popularity as a programming language of choice for researchers. It has an excellent ecosystem including the powerful RStudio development environment. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Data Carpentry. #### You'll learn: - Basic syntax and data types in R - RStudio interface - How to import CSV files into R - The structure of data frames - A brief introduction to data wrangling and data transformation - How to calculate summary statistics - A brief introduction to visualise data #### Prerequisites: No prior experience with programming needed to attend this course. **For more information, please click [here](https://intersect.org.au/training/course/r103).** 2023-06-06 13:30:00 UTC 2023-06-07 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at UNSW Online
29 - 30 August 2023
Learn to Program: R at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-unsw-online-50b0f90f-c411-49b9-9b6b-91f09b7926f3 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-08-29 13:30:00 UTC 2023-08-30 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in R at UNSW Online
5 September 2023
Data Manipulation in R at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-r-at-unsw-online-207fb64d-37b9-4cb0-8524-62e50f6e3357 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r201).** 2023-09-05 13:30:00 UTC 2023-09-05 16:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at ACU Online
26 July 2023
Data Visualisation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-acu-online Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-26 09:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Getting started with NVivo for Windows at UC Online
14 June 2023
Getting started with NVivo for Windows at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uc-online-dbb915b8-e115-46fb-aef9-fd558e4fc6e4 Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2023-06-14 09:30:00 UTC 2023-06-14 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at UC Online
28 June 2023
Excel for Researchers at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-uc-online-90109ed6-2dad-4eaa-b808-7ec0274dc6dd Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-06-28 13:30:00 UTC 2023-06-28 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Classification at Deakin Online
13 - 14 June 2023
Introduction to Machine Learning using Python: Classification at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-deakin-online-ac9ca4b5-5944-4fc7-8b40-9cc88d815c8b Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-06-13 09:30:00 UTC 2023-06-14 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at Deakin Online
27 June 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-deakin-online-87c3dbf9-000b-4b33-bdb8-9afabbc39318 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-06-27 09:30:00 UTC 2023-06-27 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in R at UNSW Online
14 June 2023
Data Visualisation in R at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-r-at-unsw-online-16a0495f-3314-4cbd-a320-c35284f8e29f R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in R](https://intersect.org.au/training/course/r201/) course. **For more information, please click [here](https://intersect.org.au/training/course/r202).** 2023-06-14 09:30:00 UTC 2023-06-14 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Classification at UTS Online
6 - 7 July 2023
Introduction to Machine Learning using Python: Classification at UTS Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uts-online-3d938199-9c5b-42a0-b8e2-10a6a714dcdb Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-07-06 10:00:00 UTC 2023-07-07 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online
14 July 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uts-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-07-14 10:00:00 UTC 2023-07-14 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: Python at UC Online
8 June 2023
Learn to Program: Python at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-uc-online-fa5c76d3-cb7a-4961-9442-947f440137ef Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-06-08 13:30:00 UTC 2023-06-08 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Getting started with HPC using PBS Pro at La Trobe Online
7 - 8 June 2023
Getting started with HPC using PBS Pro at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-hpc-using-pbs-pro-at-la-trobe-online Is your computer's limited power throttling your research ambitions? Are your analysis scripts pushing your laptop's processor to its limits? Is your software crashing because you’ve run out of memory? Would you like to unleash to power of the Unix command line to automate and run your analysis on supercomputers that you can access for free? High-Performance Computing (HPC) allows you to accomplish your analysis faster by using many parallel CPUs and huge amounts of memory simultaneously. This course provides a hands on introduction to running software on HPC infrastructure using PBS Pro. #### You'll learn: - Connect to an HPC cluster - Use the Unix command line to operate a remote computer and create job scripts - Submit and manage jobs on a cluster using a scheduler - Transfer files to and from a remote computer - Use software through environment modules - Use parallelisation to speed up data analysis - Access the facilities available to you as a researcher - This is the PBS Pro version of the Getting Started with HPC course. #### Prerequisites: This course assumes basic familiarity with the Bash command line environment found on GNU/Linux and other Unix-like environments. To come up to speed, consider taking our [Unix Shell and Command Line Basics](https://intersect.org.au/training/course/unix101/) course. **For more information, please click [here](https://intersect.org.au/training/course/hpc201).** 2023-06-07 10:00:00 UTC 2023-06-08 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at Deakin Online
6 - 7 June 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-deakin-online-0ae099b2-8220-429e-995b-e8922287bd28 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-06-06 09:30:00 UTC 2023-06-07 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at La Trobe Online
20 - 21 July 2023
Excel for Researchers at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-la-trobe-online-e67c3a36-a4fe-413b-ac35-d108f7a1532c Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-07-20 10:00:00 UTC 2023-07-21 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at La Trobe Online
15 August 2023
Data Capture and Surveys with REDCap at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-la-trobe-online-3c7b3b4e-3401-4147-93eb-46fdc58b8e22 Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-08-15 10:00:00 UTC 2023-08-15 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in Python at ACU Online
25 July 2023
Data Manipulation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-acu-online Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-25 09:30:00 UTC 2023-07-25 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Getting started with HPC using PBS Pro at La Trobe Online
22 - 23 August 2023
Getting started with HPC using PBS Pro at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-hpc-using-pbs-pro-at-la-trobe-online-d58cebff-34cd-4e46-9a56-9dc2493ea72a Is your computer's limited power throttling your research ambitions? Are your analysis scripts pushing your laptop's processor to its limits? Is your software crashing because you’ve run out of memory? Would you like to unleash to power of the Unix command line to automate and run your analysis on supercomputers that you can access for free? High-Performance Computing (HPC) allows you to accomplish your analysis faster by using many parallel CPUs and huge amounts of memory simultaneously. This course provides a hands on introduction to running software on HPC infrastructure using PBS Pro. #### You'll learn: - Connect to an HPC cluster - Use the Unix command line to operate a remote computer and create job scripts - Submit and manage jobs on a cluster using a scheduler - Transfer files to and from a remote computer - Use software through environment modules - Use parallelisation to speed up data analysis - Access the facilities available to you as a researcher - This is the PBS Pro version of the Getting Started with HPC course. #### Prerequisites: This course assumes basic familiarity with the Bash command line environment found on GNU/Linux and other Unix-like environments. To come up to speed, consider taking our [Unix Shell and Command Line Basics](https://intersect.org.au/training/course/unix101/) course. **For more information, please click [here](https://intersect.org.au/training/course/hpc201).** 2023-08-22 10:00:00 UTC 2023-08-23 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Exploring ANOVAs in R at UNE Online
6 June 2023
Exploring ANOVAs in R at UNE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/exploring-anovas-in-r-at-une-online R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. This half-day course covers one and two-way Analyses of Variance (ANOVA) and their non-parametric counterparts in R. To better understand the tests, assumptions and associated concepts, we will be using a dataset containing the Mathematics scores of secondary students. This dataset also includes information regarding their mother's and father's jobs and education levels, the number of hours dedicated to study, and time spent commuting to and from school. Lifestyle information about alcohol consumption habits, whether the students have quality relationships with their families and whether they have free time after school is included in this dataset. #### You'll learn: - Basic statistical theory behind ANOVAs - How to check that the data meets the assumptions - One-way ANOVA in R and post-hoc analysis - Two-way ANOVA plus interaction effects and post-hoc analysis - Non-parametric alternatives to one and two-way ANOVA #### Prerequisites: This course assumes an intermediate level of programming proficiency, plus familiarity with the syntax and functions of the dplyr and ggplot2 packages. Experience navigating the RStudio integrated development environment (IDE) is also required. If you’re new to programming in R, we strongly recommend you register for the [Learn to Program: R](https://intersect.org.au/training/course/r101/), [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/) workshops first. **For more information, please click [here](https://intersect.org.au/training/course/r212).** 2023-06-06 09:30:00 UTC 2023-06-06 12:30:00 UTC Intersect Australia Australia Australia UNE training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UTS Online
29 - 30 June 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at UTS Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uts-online-4c5ce68e-dbf4-4255-85d4-3b0e78527fee Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-06-29 10:00:00 UTC 2023-06-30 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at ACU Online
10 August 2023
Data Capture and Surveys with REDCap at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-acu-online-e16cb50c-6af2-4857-a651-6ec98affb128 Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-08-10 09:30:00 UTC 2023-08-10 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at UniSA
14 - 15 September 2023
Magill, Australia
Excel for Researchers at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-unisa Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-09-14 09:00:00 UTC 2023-09-15 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Beyond Basics: Conditionals and Visualisation in Excel at UniSA
27 September 2023
Magill, Australia
Beyond Basics: Conditionals and Visualisation in Excel at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-unisa After cleaning your database, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested functions, statistical charting and outlier identification. Armed with the tips and tricks from our introductory Excel for Researchers course, you will be able to tap into even more of Excel's diverse functionality and apply it to your research project. #### You'll learn: - Cell syntax and conditional formatting - IF functions - Pivot Table summaries - Nesting multiple AND/IF/OR calculations - Combining nested calculations with conditional formatting to bring out important elements of the dataset - MINIFS function - Box plot creation and outlier identification - Trendline and error bar chart enhancements #### Prerequisites: Familiarity with the content of Excel for Researchers, specifically: the general Office/Excel interface (menus, ribbons/toolbars, etc.) workbooks and worksheets absolute and relative references, e.g. $A$1, A1. simple ranges, e.g. A1:B5 **For more information, please click [here](https://intersect.org.au/training/course/excel201).** 2023-09-27 09:00:00 UTC 2023-09-27 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at La Trobe Online
20 - 21 June 2023
Learn to Program: R at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-06-20 10:00:00 UTC 2023-06-21 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at UC Online
21 June 2023
Data Visualisation in Python at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-uc-online Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-06-21 09:30:00 UTC 2023-06-21 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at La Trobe Online
8 - 9 August 2023
Data Entry and Processing in SPSS at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-la-trobe-online-289078e7-7602-434d-9320-87aeece9670d This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-08-08 10:00:00 UTC 2023-08-09 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Getting Started with NVivo for Mac at UniSA Online
5 July 2023
Getting Started with NVivo for Mac at UniSA Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unisa-online-c7d2d6a8-2125-4118-b360-8664c57573df Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-07-05 09:00:00 UTC 2023-07-05 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UniSA Online
11 - 12 July 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at UniSA Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-unisa-online-a962a590-ae7b-4b01-84f8-4e8796c98da4 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-07-11 09:00:00 UTC 2023-07-12 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at UniSA
24 - 25 October 2023
Magill, Australia
Learn to Program: R at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-unisa R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-24 09:00:00 UTC 2023-10-25 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at DPE Online
13 June 2023
Learn to Program: R at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-dpe-online R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-06-13 13:30:00 UTC 2023-06-13 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at UNE Online
8 - 9 June 2023
Data Entry and Processing in SPSS at UNE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-une-online-150553c9-2d7c-4670-a2b8-e4d6bb72f8c1 This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-06-08 09:00:00 UTC 2023-06-09 12:00:00 UTC Intersect Australia Australia Australia UNE training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: Python at UNSW Online
11 - 12 July 2023
Learn to Program: Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-unsw-online-e2c7e3dc-b38e-4e7d-83fb-645b4f89bea2 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-11 13:30:00 UTC 2023-07-12 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in R at UNSW Online
6 September 2023
Data Visualisation in R at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-r-at-unsw-online-cae0575f-6a36-4e4b-be75-c760641b3ba2 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in R](https://intersect.org.au/training/course/r201/) course. **For more information, please click [here](https://intersect.org.au/training/course/r202).** 2023-09-06 09:30:00 UTC 2023-09-06 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at ACU Online
30 - 31 August 2023
Excel for Researchers at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-acu-online-bba85166-d438-493e-9be9-5edc1770b157 Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-08-30 13:30:00 UTC 2023-08-31 16:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at UC Online
27 June 2023
Data Visualisation in Python at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-uc-online-1f89f701-1992-4011-bc11-21962db081c9 Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-06-27 09:30:00 UTC 2023-06-27 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at UC Online
26 July 2023
Data Capture and Surveys with REDCap at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uc-online-a62b1fa0-be48-409e-b669-529d8e01002e Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-07-26 13:30:00 UTC 2023-07-26 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at Deakin Online
4 - 5 July 2023
Learn to Program: R at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-deakin-online-fabc15d1-6d72-4d08-98d4-37ca23ebecea R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-07-04 09:30:00 UTC 2023-07-05 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Getting started with NVivo for Windows at La Trobe Online
15 June 2023
Getting started with NVivo for Windows at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2023-06-15 10:00:00 UTC 2023-06-15 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Classification at UniSA
26 - 27 July 2023
Magill, Australia
Introduction to Machine Learning using Python: Classification at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unisa Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-07-26 09:00:00 UTC 2023-07-27 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UniSA
11 - 12 July 2023
Magill, Australia
Introduction to Machine Learning using Python: Introduction & Linear Regression at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-unisa Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-07-11 09:00:00 UTC 2023-07-12 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Longitudinal Trials with REDCap at UniSA
13 July 2023
Magill, Australia
Longitudinal Trials with REDCap at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/longitudinal-trials-with-redcap-at-unisa REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with very little configuration. This course will introduce some of REDCap's more advanced features for running longitudinal studies, and builds on the foundational material taught in REDCAP101 - Managing Data Capture and Surveys with REDCap. #### You'll learn: - Build a longitudinal project - Manage participants throughout multiple events - Configure and use Automated Survey Invitations - Use Smart Variables to add powerful features to your logic - Take advantage of high-granularity permissions for your collaborators - Understand the data structure of a longitudinal project #### Prerequisites: This course requires the participant to have a fairly good basic knowledge of REDCap. To come up to speed, consider taking our [Data Capture and Surveys with REDCap](https://intersect.org.au/training/course/redcap101/) workshop. **For more information, please click [here](https://intersect.org.au/training/course/redcap201).** 2023-07-13 09:00:00 UTC 2023-07-13 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in Python at DPE Online
8 June 2023
Data Manipulation and Visualisation in Python at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-python-at-dpe-online-52e4e14b-1c11-4d52-887f-f6f59260d207 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation). We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python203).** 2023-06-08 13:30:00 UTC 2023-06-08 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in R at DPE Online
27 June 2023
Data Manipulation and Visualisation in R at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-dpe-online R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). You will also explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r203).** 2023-06-27 13:30:00 UTC 2023-06-27 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in R at UNSW Online
13 June 2023
Data Manipulation in R at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-r-at-unsw-online-1fc6dd79-550c-42b0-b821-de3fc262333b R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r201).** 2023-06-13 13:30:00 UTC 2023-06-13 16:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online
25 - 26 July 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-unsw-online-2cd2c52a-0ac2-42b6-8a92-803c999fb04c Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-07-25 13:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Classification at UNSW Online
1 - 2 August 2023
Introduction to Machine Learning using Python: Classification at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unsw-online-83aa5df2-8380-4bc1-92ac-590f93026d4a Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-08-01 13:30:00 UTC 2023-08-02 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Getting Started with NVivo for Mac at UniSA
5 July 2023
Magill, Australia
Getting Started with NVivo for Mac at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unisa Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-07-05 09:00:00 UTC 2023-07-05 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: Python at La Trobe Online
17 - 18 August 2023
Learn to Program: Python at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-la-trobe-online-92a2525c-3065-464c-a07d-15012fc3c5c9 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-08-17 10:00:00 UTC 2023-08-18 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in R at DPE Online
28 June 2023
Data Manipulation and Visualisation in R at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-dpe-online-d4fa67ca-f43c-4110-ab88-deb3be963025 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). You will also explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r203).** 2023-06-28 13:30:00 UTC 2023-06-28 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at DPE Online
14 June 2023
Learn to Program: R at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-dpe-online-11e9d347-a41e-4da8-80c4-e0c5ae9dda83 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-06-14 13:30:00 UTC 2023-06-14 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at ACU Online
7 July 2023
Surveying with Qualtrics at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-acu-online-173b1527-bd26-4b17-bc2c-685cdb21c8ba Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-07 09:30:00 UTC 2023-07-07 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Longitudinal Trials with REDCap at ACU Online
11 August 2023
Longitudinal Trials with REDCap at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/longitudinal-trials-with-redcap-at-acu-online-b046a8e8-d49e-473d-a44f-cad7b3597e4c REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with very little configuration. This course will introduce some of REDCap's more advanced features for running longitudinal studies, and builds on the foundational material taught in REDCAP101 - Managing Data Capture and Surveys with REDCap. #### You'll learn: - Build a longitudinal project - Manage participants throughout multiple events - Configure and use Automated Survey Invitations - Use Smart Variables to add powerful features to your logic - Take advantage of high-granularity permissions for your collaborators - Understand the data structure of a longitudinal project #### Prerequisites: This course requires the participant to have a fairly good basic knowledge of REDCap. To come up to speed, consider taking our [Data Capture and Surveys with REDCap](https://intersect.org.au/training/course/redcap101/) workshop. **For more information, please click [here](https://intersect.org.au/training/course/redcap201).** 2023-08-11 09:30:00 UTC 2023-08-11 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in R at Deakin Online
18 - 19 July 2023
Data Manipulation and Visualisation in R at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-deakin-online-3be296eb-bcd6-4b8e-92f3-b7c0fd1981f0 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). You will also explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r203).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at La Trobe Online
5 - 6 July 2023
Learn to Program: R at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online-f7f1dda5-4218-4676-858e-09bd0d61d454 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-07-05 10:00:00 UTC 2023-07-06 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at Western Sydney: Online
29 - 30 June 2023
Excel for Researchers at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-western-sydney-online-c6f02010-aeee-4b99-9895-a03d0b990d25 Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-06-29 09:30:00 UTC 2023-06-30 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at Western Sydney: Online
14 July 2023
Surveying with Qualtrics at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-western-sydney-online-39cedce4-fea0-4139-b3db-51d611c8dd36 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-14 09:30:00 UTC 2023-07-14 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
Learn to Program: R at DPE Online
13 June 2023
Learn to Program: R at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-r-at-dpe-online-4cc1bf2a-64ef-4715-80ac-5989cccf9cd5 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-06-13 09:30:00 UTC 2023-06-13 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at UNSW Online
26 - 27 September 2023
Data Entry and Processing in SPSS at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-unsw-online-2e30e320-3e91-4394-8469-cb00f4f1eb0b This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-09-26 13:30:00 UTC 2023-09-27 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at ACU Online
12 - 13 September 2023
Data Entry and Processing in SPSS at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-acu-online-5cfcd720-8c18-492b-9b4f-fd59f335c43b This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-09-12 13:30:00 UTC 2023-09-13 16:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at UC Online
27 - 28 June 2023
Excel for Researchers at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-uc-online-4fe4f392-46db-420f-9635-10cb72e5b4ed Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-06-27 13:30:00 UTC 2023-06-28 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at La Trobe Online
29 June 2023
Data Capture and Surveys with REDCap at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-la-trobe-online-325cde44-a547-4c01-842b-15a0aa01e900 Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-06-29 10:00:00 UTC 2023-06-29 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UniSA
28 July 2023
Magill, Australia
Surveying with Qualtrics at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-unisa Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-28 09:00:00 UTC 2023-07-28 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in Python at DPE Online
7 June 2023
Data Manipulation and Visualisation in Python at DPE Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-python-at-dpe-online-e12b1cc2-94a4-4d2d-89f3-98865f27df5a Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation). We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python203).** 2023-06-07 13:30:00 UTC 2023-06-07 16:30:00 UTC Intersect Australia Australia Australia DPE training@intersect.org.au [] [] [] host_institution []
