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Content provider: Intersect Australia 

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Organiser: Intersect Australia 

  • Longitudinal Trials with REDCap at UNE Online

    10 September 2024

    Longitudinal Trials with REDCap at UNE Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-une-online-99f8eaa5-18b0-42e8-b2f2-79f64de31d2b REDCap is a powerful and extensible application for managing and running longitudinal data collection activities. With powerful features such as organising data collection instruments into predefined events, you can shepherd 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\ workshop. For more information, please click [here](https://intersect.org.au/training/course/redcap201). 2024-09-10 09:30:00 UTC 2024-09-10 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at La Trobe Online

    10 - 11 September 2024

    Learn to Program: R at La Trobe Online https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online-ec19fb0d-668a-40fa-9c15-cb164f3529e6 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).** 2024-09-10 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at LTU Online

    10 - 11 September 2024

    Learn to Program: R at LTU Online https://dresa.org.au/events/learn-to-program-r-at-ltu-online-27d1ec5f-3b33-4fd1-966a-a914d3251390 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\. For more information, please click [here](https://intersect.org.au/training/course/r101). 2024-09-10 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online

    10 - 11 September 2024

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uoa-online-f7c6dc29-89e9-4801-9e51-3f03b5e8acbd 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\ and \Data Manipulation in Python\ or \Learn to Program: Python\ and \Data Manipulation and Visualisation in Python\ 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. For more information, please click [here](https://intersect.org.au/training/course/python205). 2024-09-10 13:30:00 UTC 2024-09-11 16:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at LTU Online

    11 September 2024

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-8b174e4c-17d4-4dae-ba4e-02e52cead8d5 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). 2024-09-11 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UC Online

    12 September 2024

    Data Capture and Surveys with REDCap at UC Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uc-online-84697a33-cc8e-4862-9356-e80cdb037771 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). 2024-09-12 09:30:00 UTC 2024-09-12 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Unix Shell and Command Line Basics at Deakin Online

    17 September 2024

    Unix Shell and Command Line Basics at Deakin Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-deakin-online-ed6b3575-5343-4ad1-aa96-c9796976203a 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 handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Exploring Chi-square and correlation in R at UNE Online

    17 September 2024

    Exploring Chi-square and correlation in R at UNE Online https://dresa.org.au/events/exploring-chi-square-and-correlation-in-r-at-une-online-ba37fd4a-dc9a-4392-a9a1-6101e0a5de90 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 for computing reliability and correlation (Pearson’s r, Spearman’s Rho and Kendall’s tau) in real world datasets. #### You'll learn: Obtain inferential statistics and assess data normality Manipulate data and create graphs Perform Chi-Square tests (Goodness of Fit test and Test of Independence) Perform correlations on continuous and categorical data (Pearson’s r, Spearman’s Rho and Kendall’s tau) #### Prerequisites: This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts, as well as familiarity with data manipulation (dplyr) and visualisation (ggplot2 package).  Please consider attending Intersect’s following courses to get up to speed: \Learn to Program: R\, \Data Manipulation and Visualisation in R\ For more information, please click [here](https://intersect.org.au/training/course/r210). 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Unix Shell and Command Line Basics at DU Online

    17 September 2024

    Unix Shell and Command Line Basics at DU Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-du-online 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 handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you’ll learn at this course are generally transferable to other Unix environments. #### You'll learn: Navigate and work with files and directories (folders) Use a selection of essential tools Combine data and tools to build a processing workflow Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/unix101). 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: Classification at UNSW Online

    17 - 18 September 2024

    Introduction to Machine Learning using R: Classification at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-classification-at-unsw-online-39a0ffe6-3317-4649-b1fc-42c4f55b96af 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 R programming language and its scientific computing packages. #### 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 R and its relevant packages to process real datasets, train and apply Machine Learning models. #### Prerequisites: \\Either \Learn to Program: R\ and \Data Manipulation in R\ or \Learn to Program: R\ and \Data Manipulation and Visualisation in R\needed to attend this course. If you already have experience with programming, please check the topics covered in courses above and \Introduction to ML using R: Introduction & Linear Regression\ to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.\\Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning 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.\\ For more information, please click [here](https://intersect.org.au/training/course/r206). 2024-09-17 09:30:00 UTC 2024-09-18 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Traversing t tests in R at UNE Online

    18 September 2024

    Traversing t tests in R at UNE Online https://dresa.org.au/events/traversing-t-tests-in-r-at-une-online-ac88bc8a-37b3-4428-9142-b48e46ff891e 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 reading in and manipulating data, checking assumptions, statistical tests and visualisations. This is not an advanced statistics course, but is instead designed to gently introduce you to statistical comparisons and hypothesis testing in R. #### You'll learn: Read in and manipulate data Check assumptions of t tests Perform one-sample t tests Perform two-sample t tests (Independent-samples, Paired-samples) Perform nonparametric t tests (One-sample Wilcoxon Signed Rank test, Independent-samples Mann-Whitney U test) #### Prerequisites: This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts. Please consider attending Intersect’s following courses to get up to speed: \Learn to Program: R\, \Data Manipulation and Visualisation in R\ For more information, please click [here](https://intersect.org.au/training/course/r211). 2024-09-18 09:30:00 UTC 2024-09-18 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at UC Online

    18 - 19 September 2024

    Learn to Program: Python at UC Online https://dresa.org.au/events/learn-to-program-python-at-uc-online-dd9e4087-7bec-4571-ac60-811bc7c56968 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 analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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). 2024-09-18 09:30:00 UTC 2024-09-19 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Excel for Researchers at ACU

    19 - 20 September 2024

    Introduction to Excel for Researchers at ACU https://dresa.org.au/events/introduction-to-excel-for-researchers-at-acu 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). 2024-09-19 09:30:00 UTC 2024-09-20 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: Classification at UOA Online

    19 - 20 September 2024

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-93e63532-9b9f-474a-abdd-312ac717ea9d 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\, \Data Manipulation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ or \Learn to Program: Python\, \Data Manipulation and Visualisation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ 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. For more information, please click [here](https://intersect.org.au/training/course/python206). 2024-09-19 09:30:00 UTC 2024-09-20 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Exploring ANOVAs in R at UNE Online

    19 September 2024

    Exploring ANOVAs in R at UNE Online https://dresa.org.au/events/exploring-anovas-in-r-at-une-online-fdb6b370-909e-463b-8764-d614983830eb 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\, \Data Manipulation and Visualisation in R\ workshops first.  For more information, please click [here](https://intersect.org.au/training/course/r212). 2024-09-19 09:30:00 UTC 2024-09-19 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Research Data Management at WSU Online

    19 September 2024

    Introduction to Research Data Management at WSU Online https://dresa.org.au/events/introduction-to-research-data-management-at-wsu-online-b36d9269-ff80-41df-b232-ed4ebc43e47d 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 success and are interested in research data management services and support available at their institution. Combining slide-based background material, discussions, and case studies this workshop will equip participants with best practices for managing their valuable research data. #### You'll learn: How to manage research data according to legal, statutory, ethical, funding body and university requirements Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data Services supporting research data at your institution #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/rdmt001). 2024-09-19 10:00:00 UTC 2024-09-19 12:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Research Data Management at WSU Online

    20 September 2024

    Introduction to Research Data Management at WSU Online https://dresa.org.au/events/introduction-to-research-data-management-at-wsu-online-f34668d1-7774-4ffb-8377-f93e3c3e4f37 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 success and are interested in research data management services and support available at their institution. Combining slide-based background material, discussions, and case studies this workshop will equip participants with best practices for managing their valuable research data. #### You'll learn: How to manage research data according to legal, statutory, ethical, funding body and university requirements Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data Services supporting research data at your institution #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/rdmt001). 2024-09-20 10:00:00 UTC 2024-09-20 12:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at Deakin Online

    24 - 25 September 2024

    Learn to Program: Python at Deakin Online https://dresa.org.au/events/learn-to-program-python-at-deakin-online-77251553-9eae-45c2-9810-347bcc973a3a 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 analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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).** 2024-09-24 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at DU Online

    24 - 25 September 2024

    Learn to Program: Python at DU Online https://dresa.org.au/events/learn-to-program-python-at-du-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. 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 analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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). 2024-09-24 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online

    24 September 2024

    Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-svm-unsupervised-learning-at-unsw-online-f91f1904-6c94-4dd7-a094-4fe8c5bfbbdc 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 R programming language and its scientific computing packages. #### 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 R and its relevant packages to process real datasets, train and apply Machine Learning models. #### Prerequisites: \\Either \Learn to Program: R\ and \Data Manipulation in R\ or \Learn to Program: R\ and \Data Manipulation and Visualisation in R\needed to attend this course. If you already have experience with programming, please check the topics covered in the courses above and \Introduction to ML using R: Introduction & Linear Regression\ to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.\\Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning 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.\\ For more information, please click [here](https://intersect.org.au/training/course/r207). 2024-09-24 09:30:00 UTC 2024-09-24 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Excel for Researchers at UNE Online

    24 September 2024

    Excel for Researchers at UNE Online https://dresa.org.au/events/excel-for-researchers-at-une-online-a53333b8-aeb4-4a76-8e7b-7548d1f2b2db 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). 2024-09-24 09:30:00 UTC 2024-09-24 16:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online

    25 September 2024

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-3c8179e6-cdc7-46bb-9682-895488ee732a 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\, \Data Manipulation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ or \Learn to Program: Python\, \Data Manipulation and Visualisation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ 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. For more information, please click [here](https://intersect.org.au/training/course/python207). 2024-09-25 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at UNE Online

    25 September 2024

    Surveying with Qualtrics at UNE Online https://dresa.org.au/events/surveying-with-qualtrics-at-une-online-892aa020-002c-4fd7-b0db-b9cfb34e5100 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). 2024-09-25 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at La Trobe Online

    25 September 2024

    Data Capture and Surveys with REDCap at La Trobe Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-la-trobe-online-75f47423-7ad6-45e8-b8d4-ae67f17305fc 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).** 2024-09-25 10:00:00 UTC 2024-09-25 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at LTU Online

    25 September 2024

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-202321e5-6887-4dce-bc6b-fee07ede2664 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). 2024-09-25 10:00:00 UTC 2024-09-25 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at LTU Online

    25 - 26 September 2024

    Learn to Program: R at LTU Online https://dresa.org.au/events/learn-to-program-r-at-ltu-online-909d86e9-d993-4190-886b-51f488a788d5 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\. For more information, please click [here](https://intersect.org.au/training/course/r101). 2024-09-25 10:00:00 UTC 2024-09-26 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Beyond Basics: Conditionals and Visualisation in Excel at UNE Online

    26 September 2024

    Beyond Basics: Conditionals and Visualisation in Excel at UNE Online https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-une-online-feca787b-f017-4f59-975f-b9a1c91a6d1c 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). 2024-09-26 09:30:00 UTC 2024-09-26 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at UC Online

    26 September 2024

    Getting started with NVivo for Windows at UC Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uc-online-cd8f15c3-27fc-48f9-bdf9-aba4d82a0699 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). 2024-09-26 09:30:00 UTC 2024-09-26 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Beyond Basics: Conditionals and Visualisation in Excel at ACU

    26 September 2024

    Beyond Basics: Conditionals and Visualisation in Excel at ACU https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-acu-6678191a-b7d0-4c64-864c-0ed2c6ae8b1f 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). 2024-09-26 10:00:00 UTC 2024-09-26 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at Deakin Online

    1 - 2 October 2024

    Learn to Program: R at Deakin Online https://dresa.org.au/events/learn-to-program-r-at-deakin-online-396cbea7-9de9-4a40-af11-a98c733a71a1 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).** 2024-10-01 09:30:00 UTC 2024-10-02 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Longitudinal Trials with REDCap at UNE Online

    10 September 2024

    Longitudinal Trials with REDCap at UNE Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-une-online-99f8eaa5-18b0-42e8-b2f2-79f64de31d2b REDCap is a powerful and extensible application for managing and running longitudinal data collection activities. With powerful features such as organising data collection instruments into predefined events, you can shepherd 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\ workshop. For more information, please click [here](https://intersect.org.au/training/course/redcap201). 2024-09-10 09:30:00 UTC 2024-09-10 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at La Trobe Online

    10 - 11 September 2024

    Learn to Program: R at La Trobe Online https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online-ec19fb0d-668a-40fa-9c15-cb164f3529e6 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).** 2024-09-10 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at LTU Online

    10 - 11 September 2024

    Learn to Program: R at LTU Online https://dresa.org.au/events/learn-to-program-r-at-ltu-online-27d1ec5f-3b33-4fd1-966a-a914d3251390 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\. For more information, please click [here](https://intersect.org.au/training/course/r101). 2024-09-10 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online

    10 - 11 September 2024

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uoa-online-f7c6dc29-89e9-4801-9e51-3f03b5e8acbd 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\ and \Data Manipulation in Python\ or \Learn to Program: Python\ and \Data Manipulation and Visualisation in Python\ 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. For more information, please click [here](https://intersect.org.au/training/course/python205). 2024-09-10 13:30:00 UTC 2024-09-11 16:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at LTU Online

    11 September 2024

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-8b174e4c-17d4-4dae-ba4e-02e52cead8d5 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). 2024-09-11 10:00:00 UTC 2024-09-11 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UC Online

    12 September 2024

    Data Capture and Surveys with REDCap at UC Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uc-online-84697a33-cc8e-4862-9356-e80cdb037771 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). 2024-09-12 09:30:00 UTC 2024-09-12 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Unix Shell and Command Line Basics at Deakin Online

    17 September 2024

    Unix Shell and Command Line Basics at Deakin Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-deakin-online-ed6b3575-5343-4ad1-aa96-c9796976203a 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 handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Exploring Chi-square and correlation in R at UNE Online

    17 September 2024

    Exploring Chi-square and correlation in R at UNE Online https://dresa.org.au/events/exploring-chi-square-and-correlation-in-r-at-une-online-ba37fd4a-dc9a-4392-a9a1-6101e0a5de90 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 for computing reliability and correlation (Pearson’s r, Spearman’s Rho and Kendall’s tau) in real world datasets. #### You'll learn: Obtain inferential statistics and assess data normality Manipulate data and create graphs Perform Chi-Square tests (Goodness of Fit test and Test of Independence) Perform correlations on continuous and categorical data (Pearson’s r, Spearman’s Rho and Kendall’s tau) #### Prerequisites: This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts, as well as familiarity with data manipulation (dplyr) and visualisation (ggplot2 package).  Please consider attending Intersect’s following courses to get up to speed: \Learn to Program: R\, \Data Manipulation and Visualisation in R\ For more information, please click [here](https://intersect.org.au/training/course/r210). 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Unix Shell and Command Line Basics at DU Online

    17 September 2024

    Unix Shell and Command Line Basics at DU Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-du-online 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 handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you’ll learn at this course are generally transferable to other Unix environments. #### You'll learn: Navigate and work with files and directories (folders) Use a selection of essential tools Combine data and tools to build a processing workflow Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/unix101). 2024-09-17 09:30:00 UTC 2024-09-17 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: Classification at UNSW Online

    17 - 18 September 2024

    Introduction to Machine Learning using R: Classification at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-classification-at-unsw-online-39a0ffe6-3317-4649-b1fc-42c4f55b96af 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 R programming language and its scientific computing packages. #### 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 R and its relevant packages to process real datasets, train and apply Machine Learning models. #### Prerequisites: \\Either \Learn to Program: R\ and \Data Manipulation in R\ or \Learn to Program: R\ and \Data Manipulation and Visualisation in R\needed to attend this course. If you already have experience with programming, please check the topics covered in courses above and \Introduction to ML using R: Introduction & Linear Regression\ to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.\\Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning 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.\\ For more information, please click [here](https://intersect.org.au/training/course/r206). 2024-09-17 09:30:00 UTC 2024-09-18 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Traversing t tests in R at UNE Online

    18 September 2024

    Traversing t tests in R at UNE Online https://dresa.org.au/events/traversing-t-tests-in-r-at-une-online-ac88bc8a-37b3-4428-9142-b48e46ff891e 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 reading in and manipulating data, checking assumptions, statistical tests and visualisations. This is not an advanced statistics course, but is instead designed to gently introduce you to statistical comparisons and hypothesis testing in R. #### You'll learn: Read in and manipulate data Check assumptions of t tests Perform one-sample t tests Perform two-sample t tests (Independent-samples, Paired-samples) Perform nonparametric t tests (One-sample Wilcoxon Signed Rank test, Independent-samples Mann-Whitney U test) #### Prerequisites: This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts. Please consider attending Intersect’s following courses to get up to speed: \Learn to Program: R\, \Data Manipulation and Visualisation in R\ For more information, please click [here](https://intersect.org.au/training/course/r211). 2024-09-18 09:30:00 UTC 2024-09-18 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at UC Online

    18 - 19 September 2024

    Learn to Program: Python at UC Online https://dresa.org.au/events/learn-to-program-python-at-uc-online-dd9e4087-7bec-4571-ac60-811bc7c56968 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 analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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). 2024-09-18 09:30:00 UTC 2024-09-19 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Excel for Researchers at ACU

    19 - 20 September 2024

    Introduction to Excel for Researchers at ACU https://dresa.org.au/events/introduction-to-excel-for-researchers-at-acu 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). 2024-09-19 09:30:00 UTC 2024-09-20 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: Classification at UOA Online

    19 - 20 September 2024

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-93e63532-9b9f-474a-abdd-312ac717ea9d 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\, \Data Manipulation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ or \Learn to Program: Python\, \Data Manipulation and Visualisation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ 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. For more information, please click [here](https://intersect.org.au/training/course/python206). 2024-09-19 09:30:00 UTC 2024-09-20 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Exploring ANOVAs in R at UNE Online

    19 September 2024

    Exploring ANOVAs in R at UNE Online https://dresa.org.au/events/exploring-anovas-in-r-at-une-online-fdb6b370-909e-463b-8764-d614983830eb 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\, \Data Manipulation and Visualisation in R\ workshops first.  For more information, please click [here](https://intersect.org.au/training/course/r212). 2024-09-19 09:30:00 UTC 2024-09-19 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Research Data Management at WSU Online

    19 September 2024

    Introduction to Research Data Management at WSU Online https://dresa.org.au/events/introduction-to-research-data-management-at-wsu-online-b36d9269-ff80-41df-b232-ed4ebc43e47d 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 success and are interested in research data management services and support available at their institution. Combining slide-based background material, discussions, and case studies this workshop will equip participants with best practices for managing their valuable research data. #### You'll learn: How to manage research data according to legal, statutory, ethical, funding body and university requirements Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data Services supporting research data at your institution #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/rdmt001). 2024-09-19 10:00:00 UTC 2024-09-19 12:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Research Data Management at WSU Online

    20 September 2024

    Introduction to Research Data Management at WSU Online https://dresa.org.au/events/introduction-to-research-data-management-at-wsu-online-f34668d1-7774-4ffb-8377-f93e3c3e4f37 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 success and are interested in research data management services and support available at their institution. Combining slide-based background material, discussions, and case studies this workshop will equip participants with best practices for managing their valuable research data. #### You'll learn: How to manage research data according to legal, statutory, ethical, funding body and university requirements Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data Services supporting research data at your institution #### Prerequisites: The course has no prerequisites. For more information, please click [here](https://intersect.org.au/training/course/rdmt001). 2024-09-20 10:00:00 UTC 2024-09-20 12:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at Deakin Online

    24 - 25 September 2024

    Learn to Program: Python at Deakin Online https://dresa.org.au/events/learn-to-program-python-at-deakin-online-77251553-9eae-45c2-9810-347bcc973a3a 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 analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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).** 2024-09-24 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at DU Online

    24 - 25 September 2024

    Learn to Program: Python at DU Online https://dresa.org.au/events/learn-to-program-python-at-du-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. 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 analysing multiple data sets (LOOPS) Making choices (IF STATEMENTS – CONDITIONALS) Ways to visualise data in Python #### Prerequisites: No prior experience with programming is 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). 2024-09-24 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online

    24 September 2024

    Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-svm-unsupervised-learning-at-unsw-online-f91f1904-6c94-4dd7-a094-4fe8c5bfbbdc 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 R programming language and its scientific computing packages. #### 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 R and its relevant packages to process real datasets, train and apply Machine Learning models. #### Prerequisites: \\Either \Learn to Program: R\ and \Data Manipulation in R\ or \Learn to Program: R\ and \Data Manipulation and Visualisation in R\needed to attend this course. If you already have experience with programming, please check the topics covered in the courses above and \Introduction to ML using R: Introduction & Linear Regression\ to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.\\Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning 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.\\ For more information, please click [here](https://intersect.org.au/training/course/r207). 2024-09-24 09:30:00 UTC 2024-09-24 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Excel for Researchers at UNE Online

    24 September 2024

    Excel for Researchers at UNE Online https://dresa.org.au/events/excel-for-researchers-at-une-online-a53333b8-aeb4-4a76-8e7b-7548d1f2b2db 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). 2024-09-24 09:30:00 UTC 2024-09-24 16:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online

    25 September 2024

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-3c8179e6-cdc7-46bb-9682-895488ee732a 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\, \Data Manipulation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ or \Learn to Program: Python\, \Data Manipulation and Visualisation in Python\ and \Introduction to ML using Python: Introduction & Linear Regression\ 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. For more information, please click [here](https://intersect.org.au/training/course/python207). 2024-09-25 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at UNE Online

    25 September 2024

    Surveying with Qualtrics at UNE Online https://dresa.org.au/events/surveying-with-qualtrics-at-une-online-892aa020-002c-4fd7-b0db-b9cfb34e5100 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). 2024-09-25 09:30:00 UTC 2024-09-25 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at La Trobe Online

    25 September 2024

    Data Capture and Surveys with REDCap at La Trobe Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-la-trobe-online-75f47423-7ad6-45e8-b8d4-ae67f17305fc 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).** 2024-09-25 10:00:00 UTC 2024-09-25 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at LTU Online

    25 September 2024

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-202321e5-6887-4dce-bc6b-fee07ede2664 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). 2024-09-25 10:00:00 UTC 2024-09-25 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at LTU Online

    25 - 26 September 2024

    Learn to Program: R at LTU Online https://dresa.org.au/events/learn-to-program-r-at-ltu-online-909d86e9-d993-4190-886b-51f488a788d5 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\. For more information, please click [here](https://intersect.org.au/training/course/r101). 2024-09-25 10:00:00 UTC 2024-09-26 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Beyond Basics: Conditionals and Visualisation in Excel at UNE Online

    26 September 2024

    Beyond Basics: Conditionals and Visualisation in Excel at UNE Online https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-une-online-feca787b-f017-4f59-975f-b9a1c91a6d1c 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). 2024-09-26 09:30:00 UTC 2024-09-26 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at UC Online

    26 September 2024

    Getting started with NVivo for Windows at UC Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uc-online-cd8f15c3-27fc-48f9-bdf9-aba4d82a0699 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). 2024-09-26 09:30:00 UTC 2024-09-26 12:30:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Beyond Basics: Conditionals and Visualisation in Excel at ACU

    26 September 2024

    Beyond Basics: Conditionals and Visualisation in Excel at ACU https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-acu-6678191a-b7d0-4c64-864c-0ed2c6ae8b1f 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). 2024-09-26 10:00:00 UTC 2024-09-26 13:00:00 UTC Intersect Australia Australia Australia Intersect Australia training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at Deakin Online

    1 - 2 October 2024

    Learn to Program: R at Deakin Online https://dresa.org.au/events/learn-to-program-r-at-deakin-online-396cbea7-9de9-4a40-af11-a98c733a71a1 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).** 2024-10-01 09:30:00 UTC 2024-10-02 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

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