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128 event found
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Learn to Program: Python at UNSW Online
11 - 12 July 2023
Learn to Program: Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-unsw-online-e2c7e3dc-b38e-4e7d-83fb-645b4f89bea2 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-11 13:30:00 UTC 2023-07-12 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Longitudinal and Mixed Model Analysis with R
13 July 2023
Longitudinal and Mixed Model Analysis with R https://www.qcif.edu.au/trainingcourses/longitudinal-and-mixed-model-analysis/ https://dresa.org.au/events/longitudinal-and-mixed-model-analysis-with-r-d1a7cbcd-384d-4e44-99da-c8afad8f0708 This workshop will develop participants’ understanding of the principles, methods, and interpretation of statistical models for longitudinal data (i.e. repeated measures over time) using R. The course will cover the principles of Linear Mixed Models from simple models to more complex ones and includes practical sessions getting hands-on experience of longitudinal analysis in R. 2023-07-13 09:00:00 UTC 2023-07-13 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Longitudinal Trials with REDCap at UniSA
13 July 2023
Magill, Australia
Longitudinal Trials with REDCap at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/longitudinal-trials-with-redcap-at-unisa REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with very little configuration. This course will introduce some of REDCap's more advanced features for running longitudinal studies, and builds on the foundational material taught in REDCAP101 - Managing Data Capture and Surveys with REDCap. #### You'll learn: - Build a longitudinal project - Manage participants throughout multiple events - Configure and use Automated Survey Invitations - Use Smart Variables to add powerful features to your logic - Take advantage of high-granularity permissions for your collaborators - Understand the data structure of a longitudinal project #### Prerequisites: This course requires the participant to have a fairly good basic knowledge of REDCap. To come up to speed, consider taking our [Data Capture and Surveys with REDCap](https://intersect.org.au/training/course/redcap101/) workshop. **For more information, please click [here](https://intersect.org.au/training/course/redcap201).** 2023-07-13 09:00:00 UTC 2023-07-13 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at Western Sydney: Online
14 July 2023
Surveying with Qualtrics at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-western-sydney-online-39cedce4-fea0-4139-b3db-51d611c8dd36 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-14 09:30:00 UTC 2023-07-14 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online
14 July 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uts-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-07-14 10:00:00 UTC 2023-07-14 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution [] -
Introduction to HPC
17 July 2023
Introduction to HPC https://www.qcif.edu.au/trainingcourses/introduction-to-hpc/ https://dresa.org.au/events/introduction-to-hpc-6cb779ea-dd3c-46ae-b833-52cc742a84e0 High-Performance Computing, or HPC, is the use of computers orders of magnitude faster and more powerful than even the best desktop PC. As research becomes more and more data-intensive, an ever broader range of researchers are using HPC for their data analysis. This workshop will give you an introduction to using high-performance computing systems effectively (as well as their limitations), and will introduce the basics of how to access a HPC cluster, load and use software, and submit jobs to run. 2023-07-17 09:00:00 UTC 2023-07-17 13:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop host_institution [] -
Learn to Program: Python at ACU Online
18 - 19 July 2023
Learn to Program: Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-acu-online-46a479f8-02c1-4918-a968-a3d876c6e001 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in R at Deakin Online
18 - 19 July 2023
Data Manipulation and Visualisation in R at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-deakin-online-3be296eb-bcd6-4b8e-92f3-b7c0fd1981f0 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). You will also explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r203).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in Python at UNSW Online
18 July 2023
Data Manipulation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-unsw-online-23fa1a76-a874-43a9-a2ca-11c32e78c95d Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-18 13:30:00 UTC 2023-07-18 16:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at UNSW Online
19 July 2023
Data Visualisation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-unsw-online-78c7c702-ec13-48fd-b278-3ca17824c4ae Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-19 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UC Online
20 July 2023
Surveying with Qualtrics at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-uc-online-eccd3958-481d-4aef-a64f-5735428578e9 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-20 09:30:00 UTC 2023-07-20 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at La Trobe Online
20 - 21 July 2023
Excel for Researchers at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-la-trobe-online-e67c3a36-a4fe-413b-ac35-d108f7a1532c Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-07-20 10:00:00 UTC 2023-07-21 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Programming: Plotting and Programming with Python
24 - 27 July 2023
Introduction to Programming: Plotting and Programming with Python https://www.qcif.edu.au/trainingcourses/plotting-and-programming-with-python/ https://dresa.org.au/events/introduction-to-programming-plotting-and-programming-with-python-34c34b0b-27cc-4e34-b72a-38ad655f9d42 This Software Carpentry workshop will introduce the building blocks of the Python scripting environment. Participants will start by exploring the command-line interface and basic programming concepts using Unix, before moving on to learn about simple and complex data types, conditionals and looping in Python. This workshop will prepare participants to carry out batch analysis and equip them with the knowledge to start creating automated pipelines to increase data processing power and productivity. 2023-07-24 09:00:00 UTC 2023-07-27 12:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Data Manipulation in Python at ACU Online
25 July 2023
Data Manipulation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-acu-online Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-25 09:30:00 UTC 2023-07-25 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Getting started with NVivo for Windows at La Trobe Online
25 July 2023
Getting started with NVivo for Windows at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online-1b36cbe0-b606-4ea9-af1a-2baec562ea93 Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2023-07-25 10:00:00 UTC 2023-07-25 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online
25 - 26 July 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-unsw-online-2cd2c52a-0ac2-42b6-8a92-803c999fb04c Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-07-25 13:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Management Plans Interest Group #2, 2023
25 July 2023
Data Management Plans Interest Group #2, 2023 https://www.eventbrite.com.au/e/data-management-plans-interest-group-2-2023-tickets-588956714387 https://dresa.org.au/events/data-management-plans-interest-group-2-2023 We are an Australasian interest group for people interested in discussing, building and improving Data Management Plans (DMPs). 2023-07-25 14:00:00 UTC 2023-07-25 15:00:00 UTC Australian Research Data Commons Australian Research Data Commons (ARDC) contact@ardc.edu.au [] [] 120 meeting open_to_all Science & TechnologyOther -
Introduction to Machine Learning using Python: Classification at UniSA
26 - 27 July 2023
Magill, Australia
Introduction to Machine Learning using Python: Classification at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unisa Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-07-26 09:00:00 UTC 2023-07-27 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at ACU Online
26 July 2023
Data Visualisation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-acu-online Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-26 09:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at UC Online
26 July 2023
Data Capture and Surveys with REDCap at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uc-online-a62b1fa0-be48-409e-b669-529d8e01002e Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-07-26 13:30:00 UTC 2023-07-26 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UniSA
28 July 2023
Magill, Australia
Surveying with Qualtrics at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-unisa Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-28 09:00:00 UTC 2023-07-28 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Linear Regression using SPSS
31 July 2023
Linear Regression using SPSS https://www.qcif.edu.au/trainingcourses/linear-regression-spss/ https://dresa.org.au/events/linear-regression-using-spss-d9819703-6572-4fa7-b5c8-c04a70350ea1 This workshop is designed to increase participants understanding of statistical relationships between data. It introduces principles and methods of regression models using SPSS, and how to interpret relationships between variables. The course covers basic principles of regression methods through to interpreting the output of statistical analyses, and also includes practical sessions giving hands-on experience with regression analysis in SPSS. 2023-07-31 09:00:00 UTC 2023-07-31 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Working with Sensitive Data
1 August 2023
Working with Sensitive Data https://www.qcif.edu.au/trainingcourses/working-with-sensitive-data/ https://dresa.org.au/events/working-with-sensitive-data-97fcea16-a9bc-49c6-a0e8-a8e81cc2a2b0 This workshop uses practical and discussion-based training to guide researchers about identifying what constitutes sensitive data, the risks of working with sensitive data, and how to appropriately manage those risks. It covers the 'Five Safes' framework and researchers' responsibilities, and introduces ways to promote data security and mitigate disclosure risks. 2023-08-01 09:00:00 UTC 2023-08-01 11:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] webinar open_to_all [] -
Introduction to Machine Learning using Python: Classification at UNSW Online
1 - 2 August 2023
Introduction to Machine Learning using Python: Classification at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unsw-online-83aa5df2-8380-4bc1-92ac-590f93026d4a Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-08-01 13:30:00 UTC 2023-08-02 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Introduction to Programming: R for Reproducible Scientific Analysis
7 - 10 August 2023
Introduction to Programming: R for Reproducible Scientific Analysis https://www.qcif.edu.au/trainingcourses/r-for-reproducible-scientific-analysis/ https://dresa.org.au/events/introduction-to-programming-r-for-reproducible-scientific-analysis-197dc0b4-ff7d-4855-b08a-0a2b7e007132 This Software Carpentry workshop will introduce novice programmers to the R software environment, a powerful, popular and free statistical and graphical programming language. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. The emphasis of this workshop is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. 2023-08-07 09:00:00 UTC 2023-08-10 12:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Statistical Comparisons using R
8 August 2023
Statistical Comparisons using R https://www.qcif.edu.au/trainingcourses/statistics-for-comparisons/ https://dresa.org.au/events/statistical-comparisons-using-r-5f9f17d2-30e9-4860-9abd-c4c0c32093d5 This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in R. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. 2023-08-08 09:00:00 UTC 2023-08-08 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online
8 August 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-unsw-online-293fa804-95b8-4537-b871-c8c3e44ce959 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-08-08 09:30:00 UTC 2023-08-08 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at La Trobe Online
8 - 9 August 2023
Data Entry and Processing in SPSS at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-la-trobe-online-289078e7-7602-434d-9320-87aeece9670d This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-08-08 10:00:00 UTC 2023-08-09 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at ACU Online
10 August 2023
Data Capture and Surveys with REDCap at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-acu-online-e16cb50c-6af2-4857-a651-6ec98affb128 Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-08-10 09:30:00 UTC 2023-08-10 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online
10 - 11 August 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-western-sydney-online-898158a8-78fa-4fd5-99f3-04c90abf3ce4 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-08-10 09:30:00 UTC 2023-08-11 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
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Learn to Program: Python at UNSW Online
11 - 12 July 2023
Learn to Program: Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-unsw-online-e2c7e3dc-b38e-4e7d-83fb-645b4f89bea2 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-11 13:30:00 UTC 2023-07-12 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Longitudinal and Mixed Model Analysis with R
13 July 2023
Longitudinal and Mixed Model Analysis with R https://www.qcif.edu.au/trainingcourses/longitudinal-and-mixed-model-analysis/ https://dresa.org.au/events/longitudinal-and-mixed-model-analysis-with-r-d1a7cbcd-384d-4e44-99da-c8afad8f0708 This workshop will develop participants’ understanding of the principles, methods, and interpretation of statistical models for longitudinal data (i.e. repeated measures over time) using R. The course will cover the principles of Linear Mixed Models from simple models to more complex ones and includes practical sessions getting hands-on experience of longitudinal analysis in R. 2023-07-13 09:00:00 UTC 2023-07-13 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Longitudinal Trials with REDCap at UniSA
13 July 2023
Magill, Australia
Longitudinal Trials with REDCap at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/longitudinal-trials-with-redcap-at-unisa REDCap is a powerful and extensible application for managing and running longitiudinal data collection activities. With powerful features such as organising data collections instruments into predefined events, you can shephard your participants through a complex survey at various time points with very little configuration. This course will introduce some of REDCap's more advanced features for running longitudinal studies, and builds on the foundational material taught in REDCAP101 - Managing Data Capture and Surveys with REDCap. #### You'll learn: - Build a longitudinal project - Manage participants throughout multiple events - Configure and use Automated Survey Invitations - Use Smart Variables to add powerful features to your logic - Take advantage of high-granularity permissions for your collaborators - Understand the data structure of a longitudinal project #### Prerequisites: This course requires the participant to have a fairly good basic knowledge of REDCap. To come up to speed, consider taking our [Data Capture and Surveys with REDCap](https://intersect.org.au/training/course/redcap101/) workshop. **For more information, please click [here](https://intersect.org.au/training/course/redcap201).** 2023-07-13 09:00:00 UTC 2023-07-13 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at Western Sydney: Online
14 July 2023
Surveying with Qualtrics at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-western-sydney-online-39cedce4-fea0-4139-b3db-51d611c8dd36 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-14 09:30:00 UTC 2023-07-14 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online
14 July 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UTS Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uts-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-07-14 10:00:00 UTC 2023-07-14 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution [] -
Introduction to HPC
17 July 2023
Introduction to HPC https://www.qcif.edu.au/trainingcourses/introduction-to-hpc/ https://dresa.org.au/events/introduction-to-hpc-6cb779ea-dd3c-46ae-b833-52cc742a84e0 High-Performance Computing, or HPC, is the use of computers orders of magnitude faster and more powerful than even the best desktop PC. As research becomes more and more data-intensive, an ever broader range of researchers are using HPC for their data analysis. This workshop will give you an introduction to using high-performance computing systems effectively (as well as their limitations), and will introduce the basics of how to access a HPC cluster, load and use software, and submit jobs to run. 2023-07-17 09:00:00 UTC 2023-07-17 13:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop host_institution [] -
Learn to Program: Python at ACU Online
18 - 19 July 2023
Learn to Program: Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/learn-to-program-python-at-acu-online-46a479f8-02c1-4918-a968-a3d876c6e001 Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation and Visualisation in R at Deakin Online
18 - 19 July 2023
Data Manipulation and Visualisation in R at Deakin Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-deakin-online-3be296eb-bcd6-4b8e-92f3-b7c0fd1981f0 R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework. In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to another (Data Transformation using the tidyr package). You will also explore different types of graphs and learn how to customise them using one of the most popular plotting packages in R, ggplot2 (Data Visualisation). We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from Intersect and the highly regarded Software Carpentry Foundation. #### You'll learn: - DataFrame Manipulation using the dplyr package - DataFrame Transformation using the tidyr package - Using the Grammar of Graphics to convert data into figures using the ggplot2 package - Configuring plot elements within ggplot2 - Exploring different types of plots using ggplot2 #### Prerequisites: Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [R for Research](https://intersect.org.au/training/course/r110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/r203).** 2023-07-18 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution [] -
Data Manipulation in Python at UNSW Online
18 July 2023
Data Manipulation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-unsw-online-23fa1a76-a874-43a9-a2ca-11c32e78c95d Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-18 13:30:00 UTC 2023-07-18 16:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at UNSW Online
19 July 2023
Data Visualisation in Python at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-unsw-online-78c7c702-ec13-48fd-b278-3ca17824c4ae Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-19 09:30:00 UTC 2023-07-19 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UC Online
20 July 2023
Surveying with Qualtrics at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-uc-online-eccd3958-481d-4aef-a64f-5735428578e9 Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-20 09:30:00 UTC 2023-07-20 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Excel for Researchers at La Trobe Online
20 - 21 July 2023
Excel for Researchers at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/excel-for-researchers-at-la-trobe-online-e67c3a36-a4fe-413b-ac35-d108f7a1532c Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2023-07-20 10:00:00 UTC 2023-07-21 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Programming: Plotting and Programming with Python
24 - 27 July 2023
Introduction to Programming: Plotting and Programming with Python https://www.qcif.edu.au/trainingcourses/plotting-and-programming-with-python/ https://dresa.org.au/events/introduction-to-programming-plotting-and-programming-with-python-34c34b0b-27cc-4e34-b72a-38ad655f9d42 This Software Carpentry workshop will introduce the building blocks of the Python scripting environment. Participants will start by exploring the command-line interface and basic programming concepts using Unix, before moving on to learn about simple and complex data types, conditionals and looping in Python. This workshop will prepare participants to carry out batch analysis and equip them with the knowledge to start creating automated pipelines to increase data processing power and productivity. 2023-07-24 09:00:00 UTC 2023-07-27 12:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Data Manipulation in Python at ACU Online
25 July 2023
Data Manipulation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-manipulation-in-python-at-acu-online Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with missing values and how to combine multiple datasets. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python201).** 2023-07-25 09:30:00 UTC 2023-07-25 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Getting started with NVivo for Windows at La Trobe Online
25 July 2023
Getting started with NVivo for Windows at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online-1b36cbe0-b606-4ea9-af1a-2baec562ea93 Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2023-07-25 10:00:00 UTC 2023-07-25 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online
25 - 26 July 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-unsw-online-2cd2c52a-0ac2-42b6-8a92-803c999fb04c Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-07-25 13:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Management Plans Interest Group #2, 2023
25 July 2023
Data Management Plans Interest Group #2, 2023 https://www.eventbrite.com.au/e/data-management-plans-interest-group-2-2023-tickets-588956714387 https://dresa.org.au/events/data-management-plans-interest-group-2-2023 We are an Australasian interest group for people interested in discussing, building and improving Data Management Plans (DMPs). 2023-07-25 14:00:00 UTC 2023-07-25 15:00:00 UTC Australian Research Data Commons Australian Research Data Commons (ARDC) contact@ardc.edu.au [] [] 120 meeting open_to_all Science & TechnologyOther -
Introduction to Machine Learning using Python: Classification at UniSA
26 - 27 July 2023
Magill, Australia
Introduction to Machine Learning using Python: Classification at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unisa Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-07-26 09:00:00 UTC 2023-07-27 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Data Visualisation in Python at ACU Online
26 July 2023
Data Visualisation in Python at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-visualisation-in-python-at-acu-online Course Materials #### You'll learn: - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. We also strongly recommend attending the [Data Manipulation in Python](https://intersect.org.au/training/course/python201/). **For more information, please click [here](https://intersect.org.au/training/course/python202).** 2023-07-26 09:30:00 UTC 2023-07-26 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at UC Online
26 July 2023
Data Capture and Surveys with REDCap at UC Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uc-online-a62b1fa0-be48-409e-b669-529d8e01002e Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-07-26 13:30:00 UTC 2023-07-26 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution [] -
Surveying with Qualtrics at UniSA
28 July 2023
Magill, Australia
Surveying with Qualtrics at UniSA https://intersect.org.au/training/schedule https://dresa.org.au/events/surveying-with-qualtrics-at-unisa Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you. #### You'll learn: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics #### Prerequisites: You must have access to a Qualtrics instance, such as through your university license. Speak to your local university IT or Research Office for assistance in accessing the Qualtrics instance. **For more information, please click [here](https://intersect.org.au/training/course/qltrics101).** 2023-07-28 09:00:00 UTC 2023-07-28 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution [] -
Linear Regression using SPSS
31 July 2023
Linear Regression using SPSS https://www.qcif.edu.au/trainingcourses/linear-regression-spss/ https://dresa.org.au/events/linear-regression-using-spss-d9819703-6572-4fa7-b5c8-c04a70350ea1 This workshop is designed to increase participants understanding of statistical relationships between data. It introduces principles and methods of regression models using SPSS, and how to interpret relationships between variables. The course covers basic principles of regression methods through to interpreting the output of statistical analyses, and also includes practical sessions giving hands-on experience with regression analysis in SPSS. 2023-07-31 09:00:00 UTC 2023-07-31 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Working with Sensitive Data
1 August 2023
Working with Sensitive Data https://www.qcif.edu.au/trainingcourses/working-with-sensitive-data/ https://dresa.org.au/events/working-with-sensitive-data-97fcea16-a9bc-49c6-a0e8-a8e81cc2a2b0 This workshop uses practical and discussion-based training to guide researchers about identifying what constitutes sensitive data, the risks of working with sensitive data, and how to appropriately manage those risks. It covers the 'Five Safes' framework and researchers' responsibilities, and introduces ways to promote data security and mitigate disclosure risks. 2023-08-01 09:00:00 UTC 2023-08-01 11:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] webinar open_to_all [] -
Introduction to Machine Learning using Python: Classification at UNSW Online
1 - 2 August 2023
Introduction to Machine Learning using Python: Classification at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unsw-online-83aa5df2-8380-4bc1-92ac-590f93026d4a Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python206).** 2023-08-01 13:30:00 UTC 2023-08-02 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Introduction to Programming: R for Reproducible Scientific Analysis
7 - 10 August 2023
Introduction to Programming: R for Reproducible Scientific Analysis https://www.qcif.edu.au/trainingcourses/r-for-reproducible-scientific-analysis/ https://dresa.org.au/events/introduction-to-programming-r-for-reproducible-scientific-analysis-197dc0b4-ff7d-4855-b08a-0a2b7e007132 This Software Carpentry workshop will introduce novice programmers to the R software environment, a powerful, popular and free statistical and graphical programming language. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. The emphasis of this workshop is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. 2023-08-07 09:00:00 UTC 2023-08-10 12:30:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Statistical Comparisons using R
8 August 2023
Statistical Comparisons using R https://www.qcif.edu.au/trainingcourses/statistics-for-comparisons/ https://dresa.org.au/events/statistical-comparisons-using-r-5f9f17d2-30e9-4860-9abd-c4c0c32093d5 This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in R. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. 2023-08-08 09:00:00 UTC 2023-08-08 17:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop open_to_all [] -
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online
8 August 2023
Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UNSW Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-unsw-online-293fa804-95b8-4537-b871-c8c3e44ce959 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/), [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) and [Introduction to ML using Python: Introduction & Linear Regression](https://intersect.org.au/training/course/python205/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax, basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries, and basic understanding of Machine Learning and Model Training. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python207).** 2023-08-08 09:30:00 UTC 2023-08-08 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution [] -
Data Entry and Processing in SPSS at La Trobe Online
8 - 9 August 2023
Data Entry and Processing in SPSS at La Trobe Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-entry-and-processing-in-spss-at-la-trobe-online-289078e7-7602-434d-9320-87aeece9670d This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2023-08-08 10:00:00 UTC 2023-08-09 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution [] -
Data Capture and Surveys with REDCap at ACU Online
10 August 2023
Data Capture and Surveys with REDCap at ACU Online https://intersect.org.au/training/schedule https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-acu-online-e16cb50c-6af2-4857-a651-6ec98affb128 Would you like to enable secure and reliable data collection forms and manage online surveys? Would your study benefit from web-based data entry? Research Electronic Data Capture (REDCap) might be for you. This course will introduce you to REDCap, a rapidly evolving web tool developed by researchers for researchers. REDCap features a high level of security, and a high degree of customisability for your forms and advanced user access control. It also features free, unlimited survey distribution functionality and a sophisticated export module with support for all standard statistical programs. #### You'll learn: - Get started with REDCap - Create and set up projects - Design forms and surveys using the online designer - Learn how to use branching logic, piping, and calculations - Enter data via forms and distribute surveys - Create, view and export data reports - Add collaborators and set their privileges #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/redcap101).** 2023-08-10 09:30:00 UTC 2023-08-10 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution [] -
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online
10 - 11 August 2023
Introduction to Machine Learning using Python: Introduction & Linear Regression at Western Sydney: Online https://intersect.org.au/training/schedule https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-western-sydney-online-898158a8-78fa-4fd5-99f3-04c90abf3ce4 Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Understand the difference between supervised and unsupervised Machine Learning. - Understand the fundamentals of Machine Learning. - Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training. - Understand the Machine Learning modelling workflows. - Use Python and scikit-learn to process real datasets, train and apply Machine Learning models #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation in Python](https://intersect.org.au/training/course/python201/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Data Manipulation and Visualisation in Python](https://intersect.org.au/training/course/python203/) needed to attend this course. If you already have experience with programming, please check the topics covered in courses above to ensure that you are familiar with the knowledge needed for this course, such as good understanding of Python syntax and basic programming concepts and familiarity with Pandas, Numpy and Seaborn libraries. Maths knowledge is not required. However, there is a few Math formula covered in this course and the references will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### Why do this course: - Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources. - It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning. - We do have applications on real datasets! - Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects. - Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning. For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using Python workshops: - Introduction to Machine Learning using Python: Introduction & Linear Regression - Introduction to Machine Learning using Python: Classification - Introduction to Machine Learning using Python: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/python205).** 2023-08-10 09:30:00 UTC 2023-08-11 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
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