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Organiser: Intersect Australia  or ARDC 

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

    4 - 5 October 2023

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-d4093c47-e816-465d-86c2-114d85d12d88 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).** 2023-10-04 09:30:00 UTC 2023-10-05 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at Western Sydney: Online

    5 October 2023

    Getting started with NVivo for Windows at Western Sydney: Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-western-sydney-online-dfc95a87-9afe-4e05-869d-4af448c2b4a5 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).** 2023-10-05 09:30:00 UTC 2023-10-05 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: Introduction & Linear Regression at UNSW Online

    11 - 13 October 2023

    Introduction to Machine Learning using R: Introduction & Linear Regression at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-introduction-linear-regression-at-unsw-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 R programming language and its scientific computing packages. #### 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 R and and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)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 R syntax and basic programming concepts and familiarity with dplyr, tidyr and ggplot2 packages. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r205).** 2023-10-11 09:30:00 UTC 2023-10-13 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at Deakin Online

    11 October 2023

    Surveying with Qualtrics at Deakin Online https://dresa.org.au/events/surveying-with-qualtrics-at-deakin-online-54ed13e0-a160-492f-b675-6ab63464dc07 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).** 2023-10-11 09:30:00 UTC 2023-10-11 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at Western Sydney: Online

    11 October 2023

    Data Capture and Surveys with REDCap at Western Sydney: Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-western-sydney-online-dc42896e-164b-4a24-a35f-85cc3395a041 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).** 2023-10-11 09:30:00 UTC 2023-10-11 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []

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

    11 - 12 October 2023

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-220e8b2d-98f6-4cd5-b649-bd59e78b3195 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).** 2023-10-11 09:30:00 UTC 2023-10-12 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Longitudinal Trials with REDCap at La Trobe Online

    11 October 2023

    Longitudinal Trials with REDCap at La Trobe Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-la-trobe-online-1ad78bea-39b8-40b6-a9c5-31696c223413 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).** 2023-10-11 10:00:00 UTC 2023-10-11 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

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

    12 October 2023

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-3a9e5ef0-1a71-4e77-afbf-3748f915a7cf 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).** 2023-10-12 09:30:00 UTC 2023-10-12 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at ACU Online

    17 - 18 October 2023

    Learn to Program: Python at ACU Online https://dresa.org.au/events/learn-to-program-python-at-acu-online-347d2cb5-a609-4d51-9c05-534c9253090f Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-10-17 09:30:00 UTC 2023-10-18 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

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

    18 - 20 October 2023

    Introduction to Machine Learning using R: Classification at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-classification-at-unsw-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use R and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)needed to attend this course. If you already have experience with programming, please check the topics covered in courses above and [Introduction to ML using R: Introduction & Linear Regression](https://intersect.org.au/training/course/r205/) to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r206).** 2023-10-18 09:30:00 UTC 2023-10-20 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at La Trobe Online

    18 October 2023

    Getting started with NVivo for Windows at La Trobe Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online-a3dd8958-ebcc-45e5-8332-af973d8883b1 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).** 2023-10-18 10:00:00 UTC 2023-10-18 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

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

    19 October 2023

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-ce2ed889-d55b-4cd9-a8d2-3ff96c96744f 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).** 2023-10-19 09:30:00 UTC 2023-10-19 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at UniSA

    24 - 25 October 2023

    Magill, Australia

    Learn to Program: R at UniSA https://dresa.org.au/events/learn-to-program-r-at-unisa R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-24 09:00:00 UTC 2023-10-25 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at UniSA Online

    24 - 25 October 2023

    Learn to Program: R at UniSA Online https://dresa.org.au/events/learn-to-program-r-at-unisa-online-5a191b52-9d3e-4fda-a892-6efecfb725f9 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-24 09:00:00 UTC 2023-10-25 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UOA Online

    24 October 2023

    Data Capture and Surveys with REDCap at UOA Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uoa-online-47c1ad90-65ea-42ee-988f-bb1b82913394 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).** 2023-10-24 09:30:00 UTC 2023-10-24 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

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

    25 October 2023

    Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-svm-unsupervised-learning-at-unsw-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use R and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)needed to attend this course. If you already have experience with programming, please check the topics covered in the courses above and [Introduction to ML using R: Introduction & Linear Regression](https://intersect.org.au/training/course/r205/) to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r207).** 2023-10-25 09:30:00 UTC 2023-10-25 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UNSW Online

    25 October 2023

    Getting Started with NVivo for Mac at UNSW Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unsw-online-190a561d-cb6f-40ba-872c-ae529dfc558e Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-10-25 09:30:00 UTC 2023-10-25 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Data Manipulation and Visualisation in Python at ACU Online

    25 - 26 October 2023

    Data Manipulation and Visualisation in Python at ACU Online https://dresa.org.au/events/data-manipulation-and-visualisation-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. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation). We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python203).** 2023-10-25 09:30:00 UTC 2023-10-26 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

  • Data Manipulation and Visualisation in R at La Trobe Online

    25 - 26 October 2023

    Data Manipulation and Visualisation in R at La Trobe Online https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-la-trobe-online-d8299a46-d875-4a83-b606-f9dc43363bed 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).** 2023-10-25 10:00:00 UTC 2023-10-26 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at UniSA Online

    25 October 2023

    Getting started with NVivo for Windows at UniSA Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-unisa-online-d55a94a4-8e83-418a-9ac9-ae8853aeb193 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).** 2023-10-25 13:00:00 UTC 2023-10-25 16:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UniSA Online

    26 October 2023

    Getting Started with NVivo for Mac at UniSA Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unisa-online-957886f8-4f00-4dac-b949-bde4f9012bfc Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-10-26 09:00:00 UTC 2023-10-26 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UTS Online

    27 October 2023

    Data Capture and Surveys with REDCap at UTS Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uts-online-7cfaa572-4f76-4be4-b3c6-0e20324024f2 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).** 2023-10-27 09:30:00 UTC 2023-10-27 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UTS Online

    27 October 2023

    Data Capture and Surveys with REDCap at UTS Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uts-online-4fc918c7-08ad-42d0-8890-952c1457b01f 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).** 2023-10-27 13:30:00 UTC 2023-10-27 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

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

    31 October - 1 November 2023

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UTS Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uts-online-87c07a0c-5058-4506-b533-1361e9f6141e 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).** 2023-10-31 09:30:00 UTC 2023-11-01 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at La Trobe Online

    31 October - 1 November 2023

    Learn to Program: R at La Trobe Online https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online-8bec5343-ccc0-40a4-b1a4-f27dcedb9ea3 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-31 10:00:00 UTC 2023-11-01 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at UNSW Online

    1 - 3 November 2023

    Learn to Program: Python at UNSW Online https://dresa.org.au/events/learn-to-program-python-at-unsw-online-24c261b5-4730-447b-895c-102ff832ab3a Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-11-01 09:30:00 UTC 2023-11-03 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

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

    1 November 2023

    Beyond Basics: Conditionals and Visualisation in Excel at ACU Online https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-acu-online After cleaning your database, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested functions, statistical charting and outlier identification. Armed with the tips and tricks from our introductory Excel for Researchers course, you will be able to tap into even more of Excel's diverse functionality and apply it to your research project. #### You'll learn: - Cell syntax and conditional formatting - IF functions - Pivot Table summaries - Nesting multiple AND/IF/OR calculations - Combining nested calculations with conditional formatting to bring out important elements of the dataset - MINIFS function - Box plot creation and outlier identification - Trendline and error bar chart enhancements #### Prerequisites: Familiarity with the content of Excel for Researchers, specifically: the general Office/Excel interface (menus, ribbons/toolbars, etc.) workbooks and worksheets absolute and relative references, e.g. $A$1, A1. simple ranges, e.g. A1:B5 **For more information, please click [here](https://intersect.org.au/training/course/excel201).** 2023-11-01 13:30:00 UTC 2023-11-01 16:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

  • Longitudinal Trials with REDCap at UTS Online

    7 November 2023

    Longitudinal Trials with REDCap at UTS Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-uts-online 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).** 2023-11-07 09:30:00 UTC 2023-11-07 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at UniSA Online

    8 November 2023

    Surveying with Qualtrics at UniSA Online https://dresa.org.au/events/surveying-with-qualtrics-at-unisa-online-99fb0249-4297-4336-977e-bd7e2a94e912 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).** 2023-11-08 09:00:00 UTC 2023-11-08 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UNSW Online

    8 November 2023

    Getting Started with NVivo for Mac at UNSW Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unsw-online Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-11-08 09:30:00 UTC 2023-11-08 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

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

    4 - 5 October 2023

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-d4093c47-e816-465d-86c2-114d85d12d88 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).** 2023-10-04 09:30:00 UTC 2023-10-05 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at Western Sydney: Online

    5 October 2023

    Getting started with NVivo for Windows at Western Sydney: Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-western-sydney-online-dfc95a87-9afe-4e05-869d-4af448c2b4a5 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).** 2023-10-05 09:30:00 UTC 2023-10-05 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []

  • Introduction to Machine Learning using R: Introduction & Linear Regression at UNSW Online

    11 - 13 October 2023

    Introduction to Machine Learning using R: Introduction & Linear Regression at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-introduction-linear-regression-at-unsw-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 R programming language and its scientific computing packages. #### 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 R and and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)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 R syntax and basic programming concepts and familiarity with dplyr, tidyr and ggplot2 packages. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r205).** 2023-10-11 09:30:00 UTC 2023-10-13 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at Deakin Online

    11 October 2023

    Surveying with Qualtrics at Deakin Online https://dresa.org.au/events/surveying-with-qualtrics-at-deakin-online-54ed13e0-a160-492f-b675-6ab63464dc07 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).** 2023-10-11 09:30:00 UTC 2023-10-11 12:30:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at Western Sydney: Online

    11 October 2023

    Data Capture and Surveys with REDCap at Western Sydney: Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-western-sydney-online-dc42896e-164b-4a24-a35f-85cc3395a041 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).** 2023-10-11 09:30:00 UTC 2023-10-11 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []

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

    11 - 12 October 2023

    Introduction to Machine Learning using Python: Classification at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-uoa-online-220e8b2d-98f6-4cd5-b649-bd59e78b3195 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).** 2023-10-11 09:30:00 UTC 2023-10-12 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Longitudinal Trials with REDCap at La Trobe Online

    11 October 2023

    Longitudinal Trials with REDCap at La Trobe Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-la-trobe-online-1ad78bea-39b8-40b6-a9c5-31696c223413 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).** 2023-10-11 10:00:00 UTC 2023-10-11 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

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

    12 October 2023

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-3a9e5ef0-1a71-4e77-afbf-3748f915a7cf 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).** 2023-10-12 09:30:00 UTC 2023-10-12 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at ACU Online

    17 - 18 October 2023

    Learn to Program: Python at ACU Online https://dresa.org.au/events/learn-to-program-python-at-acu-online-347d2cb5-a609-4d51-9c05-534c9253090f Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-10-17 09:30:00 UTC 2023-10-18 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

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

    18 - 20 October 2023

    Introduction to Machine Learning using R: Classification at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-classification-at-unsw-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use R and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)needed to attend this course. If you already have experience with programming, please check the topics covered in courses above and [Introduction to ML using R: Introduction & Linear Regression](https://intersect.org.au/training/course/r205/) to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r206).** 2023-10-18 09:30:00 UTC 2023-10-20 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at La Trobe Online

    18 October 2023

    Getting started with NVivo for Windows at La Trobe Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-la-trobe-online-a3dd8958-ebcc-45e5-8332-af973d8883b1 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).** 2023-10-18 10:00:00 UTC 2023-10-18 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

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

    19 October 2023

    Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-svm-unsupervised-learning-at-uoa-online-ce2ed889-d55b-4cd9-a8d2-3ff96c96744f 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).** 2023-10-19 09:30:00 UTC 2023-10-19 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at UniSA

    24 - 25 October 2023

    Magill, Australia

    Learn to Program: R at UniSA https://dresa.org.au/events/learn-to-program-r-at-unisa R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-24 09:00:00 UTC 2023-10-25 12:00:00 UTC Intersect Australia UniSA, Magill, Australia UniSA Magill Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at UniSA Online

    24 - 25 October 2023

    Learn to Program: R at UniSA Online https://dresa.org.au/events/learn-to-program-r-at-unisa-online-5a191b52-9d3e-4fda-a892-6efecfb725f9 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-24 09:00:00 UTC 2023-10-25 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UOA Online

    24 October 2023

    Data Capture and Surveys with REDCap at UOA Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uoa-online-47c1ad90-65ea-42ee-988f-bb1b82913394 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).** 2023-10-24 09:30:00 UTC 2023-10-24 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

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

    25 October 2023

    Introduction to Machine Learning using R: SVM & Unsupervised Learning at UNSW Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-svm-unsupervised-learning-at-unsw-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction. - Know the differences between various core Machine Learning models. - Understand the Machine Learning modelling workflows. - Use R and its relevant packages to process real datasets, train and apply Machine Learning models #### Prerequisites: - Either [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation in R](https://intersect.org.au/training/course/r201/) or [Learn to Program: R](https://intersect.org.au/training/course/r101/) and [Data Manipulation and Visualisation in R](https://intersect.org.au/training/course/r203/)needed to attend this course. If you already have experience with programming, please check the topics covered in the courses above and [Introduction to ML using R: Introduction & Linear Regression](https://intersect.org.au/training/course/r205/) to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training. - Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them. #### 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 R workshops: - Introduction to Machine Learning using R: Introduction & Linear Regression - Introduction to Machine Learning using R: Classification - Introduction to Machine Learning using R: SVM & Unsupervised Learning **For more information, please click [here](https://intersect.org.au/training/course/r207).** 2023-10-25 09:30:00 UTC 2023-10-25 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UNSW Online

    25 October 2023

    Getting Started with NVivo for Mac at UNSW Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unsw-online-190a561d-cb6f-40ba-872c-ae529dfc558e Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-10-25 09:30:00 UTC 2023-10-25 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

  • Data Manipulation and Visualisation in Python at ACU Online

    25 - 26 October 2023

    Data Manipulation and Visualisation in Python at ACU Online https://dresa.org.au/events/data-manipulation-and-visualisation-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. You will also explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation). We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Working with pandas DataFrames - Indexing, slicing and subsetting in pandas DataFrames - Missing data values - Combine multiple pandas DataFrames - Using the Grammar of Graphics to convert data into figures using the seaborn and matplotlib libraries - Configuring plot elements within seaborn and matplotlib - Exploring different types of plots using seaborn #### Prerequisites: Either [Learn to Program: Python](https://intersect.org.au/training/course/python101/) or [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) needed to attend this course. If you already have experience with programming, please check the topics covered in the [Learn to Program: Python](https://intersect.org.au/training/course/python101/) and [Python for Research](https://intersect.org.au/training/course/python110/) courses to ensure that you are familiar with the knowledge needed for this course. **For more information, please click [here](https://intersect.org.au/training/course/python203).** 2023-10-25 09:30:00 UTC 2023-10-26 12:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

  • Data Manipulation and Visualisation in R at La Trobe Online

    25 - 26 October 2023

    Data Manipulation and Visualisation in R at La Trobe Online https://dresa.org.au/events/data-manipulation-and-visualisation-in-r-at-la-trobe-online-d8299a46-d875-4a83-b606-f9dc43363bed 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).** 2023-10-25 10:00:00 UTC 2023-10-26 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Getting started with NVivo for Windows at UniSA Online

    25 October 2023

    Getting started with NVivo for Windows at UniSA Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-unisa-online-d55a94a4-8e83-418a-9ac9-ae8853aeb193 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).** 2023-10-25 13:00:00 UTC 2023-10-25 16:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UniSA Online

    26 October 2023

    Getting Started with NVivo for Mac at UniSA Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unisa-online-957886f8-4f00-4dac-b949-bde4f9012bfc Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-10-26 09:00:00 UTC 2023-10-26 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UTS Online

    27 October 2023

    Data Capture and Surveys with REDCap at UTS Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uts-online-7cfaa572-4f76-4be4-b3c6-0e20324024f2 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).** 2023-10-27 09:30:00 UTC 2023-10-27 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Data Capture and Surveys with REDCap at UTS Online

    27 October 2023

    Data Capture and Surveys with REDCap at UTS Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-uts-online-4fc918c7-08ad-42d0-8890-952c1457b01f 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).** 2023-10-27 13:30:00 UTC 2023-10-27 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

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

    31 October - 1 November 2023

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UTS Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uts-online-87c07a0c-5058-4506-b533-1361e9f6141e 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).** 2023-10-31 09:30:00 UTC 2023-11-01 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: R at La Trobe Online

    31 October - 1 November 2023

    Learn to Program: R at La Trobe Online https://dresa.org.au/events/learn-to-program-r-at-la-trobe-online-8bec5343-ccc0-40a4-b1a4-f27dcedb9ea3 R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework. But getting started with R can be challenging, particularly if you've never programmed before. That's where this introductory course comes in. We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly. Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the RStudio interface for programming - Basic syntax and data types in R - How to load external data into R - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in R #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/r101).** 2023-10-31 10:00:00 UTC 2023-11-01 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []

  • Learn to Program: Python at UNSW Online

    1 - 3 November 2023

    Learn to Program: Python at UNSW Online https://dresa.org.au/events/learn-to-program-python-at-unsw-online-24c261b5-4730-447b-895c-102ff832ab3a Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and analysing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming is needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2023-11-01 09:30:00 UTC 2023-11-03 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

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

    1 November 2023

    Beyond Basics: Conditionals and Visualisation in Excel at ACU Online https://dresa.org.au/events/beyond-basics-conditionals-and-visualisation-in-excel-at-acu-online After cleaning your database, you may need to apply some conditional analysis to glean greater insights from your data. You may also want to enhance your charts for inclusion into a manuscript, thesis or report by adding some statistical elements. This course will cover conditional syntax, nested functions, statistical charting and outlier identification. Armed with the tips and tricks from our introductory Excel for Researchers course, you will be able to tap into even more of Excel's diverse functionality and apply it to your research project. #### You'll learn: - Cell syntax and conditional formatting - IF functions - Pivot Table summaries - Nesting multiple AND/IF/OR calculations - Combining nested calculations with conditional formatting to bring out important elements of the dataset - MINIFS function - Box plot creation and outlier identification - Trendline and error bar chart enhancements #### Prerequisites: Familiarity with the content of Excel for Researchers, specifically: the general Office/Excel interface (menus, ribbons/toolbars, etc.) workbooks and worksheets absolute and relative references, e.g. $A$1, A1. simple ranges, e.g. A1:B5 **For more information, please click [here](https://intersect.org.au/training/course/excel201).** 2023-11-01 13:30:00 UTC 2023-11-01 16:30:00 UTC Intersect Australia Australia Australia ACU training@intersect.org.au [] [] [] host_institution []

  • Longitudinal Trials with REDCap at UTS Online

    7 November 2023

    Longitudinal Trials with REDCap at UTS Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-uts-online 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).** 2023-11-07 09:30:00 UTC 2023-11-07 12:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []

  • Surveying with Qualtrics at UniSA Online

    8 November 2023

    Surveying with Qualtrics at UniSA Online https://dresa.org.au/events/surveying-with-qualtrics-at-unisa-online-99fb0249-4297-4336-977e-bd7e2a94e912 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).** 2023-11-08 09:00:00 UTC 2023-11-08 12:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []

  • Getting Started with NVivo for Mac at UNSW Online

    8 November 2023

    Getting Started with NVivo for Mac at UNSW Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-unsw-online Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Mac and is not suitable for NVivo for Windows users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo102).** 2023-11-08 09:30:00 UTC 2023-11-08 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []

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