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  • Learn to Program: Python at UNSW Online

    27 - 28 September 2022

    Learn to Program: Python at UNSW Online https://dresa.org.au/events/learn-to-program-python-at-unsw-online-7ae6e87c-4d3e-4850-a04c-d47ef535cc2b Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2022-09-27 09:30:00 UTC 2022-09-28 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online

    27 - 28 September 2022

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uoa-online 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).** 2022-09-27 09:30:00 UTC 2022-09-28 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []
  • Data Capture and Surveys with REDCap at LTU Online

    27 September 2022

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-db69a609-d9bc-4cae-b683-f3de30404c0a 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).** 2022-09-27 10:00:00 UTC 2022-09-27 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Classification at UniSA Online

    27 - 28 September 2022

    Introduction to Machine Learning using Python: Classification at UniSA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unisa-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as 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).** 2022-09-27 13:00:00 UTC 2022-09-28 16:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []
  • Introduction to R for biologists

    28 September 2022

    North Melbourne, Australia

    Introduction to R for biologists https://dresa.org.au/events/introduction-to-r-for-biologists This workshop has been developed collaboratively by training specialists at Peter MacCallum Cancer Center and Melbourne Bioinformatics. This introduction to R and RStudio will provide beginners with experience with loading, manipulating and visualising biological data using the tidyverse collection of R packages. The example data used is publicly available RNA-seq data, therefore attendees will gain experience in the structure and appearance of RNA-seq data. 2022-09-28 10:00:00 UTC 2022-09-28 13:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of Melbourne bioinformatics-training@unimelb.edu.au [] beginnersLife scientists planning or running single cell RNAseq experiments (or mining public data), who want to perform their own analyses.Researchers and research students, or anyone who wants to learn intermediate statistical concepts to apply in R. 20 workshop host_institution RIntroductoryRNASeq
  • Data Entry and Processing in SPSS at UC Online

    29 - 30 September 2022

    Data Entry and Processing in SPSS at UC Online https://dresa.org.au/events/data-entry-and-processing-in-spss-at-uc-online-98ea1703-18fb-4677-af88-211451186b8c This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2022-09-29 09:30:00 UTC 2022-09-30 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Getting Started with NVivo for Mac at Western Sydney: Online

    29 September 2022

    Getting Started with NVivo for Mac at Western Sydney: Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-western-sydney-online-bafaf279-fd15-4e7a-86d1-dd5d382b63b5 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).** 2022-09-29 09:30:00 UTC 2022-09-29 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
  • Data Capture and Surveys with REDCap at LTU Online

    29 September 2022

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-0c5f113e-e32d-4d2f-be91-4624b80e9cc4 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).** 2022-09-29 10:00:00 UTC 2022-09-29 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Network analysis of differentially-expressed genes using vissE and Cytoscape

    29 September 2022

    North Melbourne, Australia

    Network analysis of differentially-expressed genes using vissE and Cytoscape https://dresa.org.au/events/network-analysis-of-differentially-expressed-genes-using-visse-and-cytoscape In biological data, similarity between genes/proteins can be exploited to identify biological functions or pathways. For example, investigating pairwise protein-protein interactions can help us identify protein complexes that have related functions. Such analyses require pairwise interaction or similarity data to be represented as a biological network. Once generated, networks can be used to investigate various structural and topological characteristics to identify key entities in the network. A popular and powerful tool to visualise and analyse biological networks is Cytoscape. This workshop is in two parts. First, using an RNAseq data set from human cancer you will use the vissE tool analyse a list of differentially-expressed (DE) genes and generate a PPI network. In the second half you will be introduced to Cytoscape interface and learn how biological networks can be uploaded and analysed in Cytoscape. 2022-09-29 10:30:00 UTC 2022-09-29 15:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of MelbourneMelbourne Bioinformatics bioinformatics-training@unimelb.edu.au [] beginnersResearchers and research students, or anyone who wants to learn intermediate statistical concepts to apply in R. 20 workshop host_institution CytoscapevissEgene listsNetworks
  • Getting started with NVivo for Windows at UNE Online

    30 September 2022

    Getting started with NVivo for Windows at UNE Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-une-online Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2022-09-30 09:30:00 UTC 2022-09-30 12:30:00 UTC Intersect Australia Australia Australia UNE training@intersect.org.au [] [] [] host_institution []
  • Unix Shell and Command Line Basics at UTS Online

    30 September 2022

    Unix Shell and Command Line Basics at UTS Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-uts-online-18e59a6f-4e60-43a6-82f6-d441e8c9e941 The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2022-09-30 10:00:00 UTC 2022-09-30 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Unix Shell and Command Line Basics at LTU Online

    30 September 2022

    Unix Shell and Command Line Basics at LTU Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-ltu-online-ddac198e-04d0-42b2-b604-85b8cbbe691a The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2022-09-30 10:00:00 UTC 2022-09-30 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Classification at UOA Online

    4 - 5 October 2022

    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 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).** 2022-10-04 09:30:00 UTC 2022-10-05 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []
  • Introduction to UNIX

    4 October 2022

    North Melbourne, Australia

    Introduction to UNIX https://dresa.org.au/events/introduction-to-unix-9a3165bd-34a3-4870-94e4-4c2e1f8b4d26 Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on an HPC system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises. Completion of this workshop will provide the background knowledge required for other Melbourne Bioinformatics workshops that require command-line skills. 2022-10-04 10:00:00 UTC 2022-10-04 14:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of Melbourne bioinformatics-training@unimelb.edu.au [] beginners 20 workshop host_institution Unix
  • Longitudinal Trials with REDCap at LTU Online

    4 October 2022

    Longitudinal Trials with REDCap at LTU Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-ltu-online-fab74bbb-894b-4e69-8157-2498a9138206 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).** 2022-10-04 10:00:00 UTC 2022-10-04 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Data Entry and Processing in SPSS at UC Online

    4 - 5 October 2022

    Data Entry and Processing in SPSS at UC Online https://dresa.org.au/events/data-entry-and-processing-in-spss-at-uc-online-2ad49709-9422-4151-b2b5-47e7e0ba5976 This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2022-10-04 13:30:00 UTC 2022-10-05 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Design and Analysis of Surveys 1: Best Practice

    5 October 2022

    Design and Analysis of Surveys 1: Best Practice https://dresa.org.au/events/design-and-analysis-of-surveys-1-best-practice This workshop is full of practical tips and guidelines on how to design, field and analyse standard surveys. Some of the topics considered will be: how to design a survey, line vs discrete scales, the effect of colour, optimal discrete/LIKERT scales, pros and cons of common analyses (e.g. linear and logistic regression) and optimal ways to export data. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 09:30:00 UTC 2022-10-05 11:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Design and Analysis of Surveys 1: Advanced Topics

    5 October 2022

    Design and Analysis of Surveys 1: Advanced Topics https://dresa.org.au/events/design-and-analysis-of-surveys-1-advanced-topics This workshop builds on the material in Surveys 1. It explores questionnaire validation and index creation using methods such as: Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) using Structural Equation Modelling (SEM), and Conjoint models such as Choice modelling. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 11:30:00 UTC 2022-10-05 13:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Design and Analysis of Surveys 2: Advanced Topics

    5 October 2022

    Design and Analysis of Surveys 2: Advanced Topics https://dresa.org.au/events/design-and-analysis-of-surveys-2-advanced-topics This workshop builds on the material in Surveys 1. It explores questionnaire validation and index creation using methods such as: Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) using Structural Equation Modelling (SEM), and Conjoint models such as Choice modelling. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 11:30:00 UTC 2022-10-05 13:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Multivariate Statistical Analysis 1: Dimension Reduction

    5 October 2022

    Multivariate Statistical Analysis 1: Dimension Reduction https://dresa.org.au/events/multivariate-statistical-analysis-1-dimension-reduction-5209a7a6-36ba-4a48-923d-58f236456361 **Multivariate Statistical Analysis 1: Dimension Reduction** In multivariate statistics we simultaneously model and estimate variability in more than one variable often in order to examine the relationship between variables. This workshop examines the key aspects of moving from univariate to multivariate analysis, and the situations and scenarios where multivariate analysis is typically applied. The focus will be on practical application of concepts through examples. **Topics covered will include:** - Motivations for undertaking multivariate analysis - Statistical principles for multivariate analysis - Dimension reduction techniques including principal components analysis (PCA), factor analysis (FA), correspondence analysis (CA) and non-metric multidimensional scaling (nMDS) This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Pre-requisites** Prior experience with statistical modelling is assumed, as the basics of regression modelling will not be covered. Please consider attending Linear Models 1 and/or Linear Models 2 workshops to come up to speed beforehand. Note that this workshop does not require knowledge of or use of specific statistics software. The analysis methods may be performed using a wide range of commonly available software. **Attendance options** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person**: Choose the _**In person**_ ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online**: Choose the _**Online Zoom**_ ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date. Sydney Informatics Hub - Open to: Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey) - Please use your University of Sydney email address to register i.e. @sydney.edu.au, @uni.sydney.edu.au, etc - If you do not have a UniKey, please contact us to confirm your position after registration. **Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you!!!** 2022-10-05 14:00:00 UTC 2022-10-05 15:30:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Introduction to Machine Learning using R: Introduction & Linear Regression at UniSA Online

    6 - 7 October 2022

    Introduction to Machine Learning using R: Introduction & Linear Regression at UniSA Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-introduction-linear-regression-at-unisa-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).** 2022-10-06 09:30:00 UTC 2022-10-07 12:30:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []
  • QIIME2 analysis of 16S rRNA

    6 October 2022

    North Melbourne, Australia

    QIIME2 analysis of 16S rRNA https://dresa.org.au/events/qiime2-analysis-of-16s-rrna This workshop will give you an introduction to the QIIME2 analysis platform using 16S rRNA amplicon data from coral-associated bacteria. 2022-10-06 10:00:00 UTC 2022-10-06 14:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of MelbourneMelbourne Bioinformatics bioinformatics-training@unimelb.edu.au [] researcherspeople with command line experience 20 workshop host_institution Qiime2Metabarcoding
  • Intro to REDCap (webinar)

    6 October 2022

    Intro to REDCap (webinar) https://dresa.org.au/events/intro-to-redcap-webinar Research Electronic Data Capture (REDCap) is a secure web-based database application maintained by the University of Sydney. It is ideal for collecting and managing participant data and administering online surveys, with features supporting longitudinal data collection, complex team workflows and exports to a range of statistical analysis programs. **In "Intro to REDCap", we will cover:** - How to build a simple data entry project - How to collect data - How to add users/collaborators - How to export data Please note we will **not cover surveys**, as these are covered separately in our "Surveys in REDCap" training session. **Target audience:** Students and staff at the University of Sydney who need to collect electronic data or responses from participants into a structured database. **Open to:** Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey). If you do not have a UniKey, please contact us to confirm your position after registration. Please use your University of Sydney email address to register (e.g. first.last@sydney.edu.au, abcd1234@uni.sydney.edu.au) **Accessing the webinar:** Your confirmation **email from Eventbrite** will contain a button which will provide the details to access the Zoom webinar **For more information:** digital.research@sydney.edu.au Sydney Informatics Hub offers a broad range of training to researchers at the University. Please see our [training site](https://sydney.edu.au/research/facilities/sydney-informatics-hub/workshops-and-training.html)for more information. 2022-10-06 10:00:00 UTC 2022-10-06 12:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Excel for Researchers at Deakin Online

    6 - 7 October 2022

    Excel for Researchers at Deakin Online https://dresa.org.au/events/excel-for-researchers-at-deakin-online-bab9bfd3-9f50-4b1a-bd93-612966314ddd Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2022-10-06 13:00:00 UTC 2022-10-07 16:00:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at UTS Online

    6 October 2022

    Getting started with NVivo for Windows at UTS Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uts-online-b28faf2f-9fd5-4807-b81e-314757189cfc 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).** 2022-10-06 13:30:00 UTC 2022-10-06 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Version Control with Git at UC Online

    6 October 2022

    Version Control with Git at UC Online https://dresa.org.au/events/version-control-with-git-at-uc-online Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there to answer all your questions while you gain hands on experience in using Git, one of the most popular version control systems available. Join us for this workshop where we cover the fundamentals of version control using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - keep versions of data, scripts, and other files - examine commit logs to find which files were changed when - restore earlier versions of files - compare changes between versions of a file - push your versioned files to a remote location, for backup and to facilitate collaboration #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/git101).** 2022-10-06 13:30:00 UTC 2022-10-06 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at Western Sydney: Online

    7 October 2022

    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-553d211b-e146-4d09-9cd0-e8deed4614fb 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).** 2022-10-07 09:30:00 UTC 2022-10-07 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at UTS Online

    7 October 2022

    Getting started with NVivo for Windows at UTS Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uts-online-3b35237e-2329-460c-b21d-edb3e4005185 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).** 2022-10-07 13:30:00 UTC 2022-10-07 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Introduction to Reproducible Research

    11 October 2022

    Introduction to Reproducible Research https://dresa.org.au/events/introduction-to-reproducible-research-40989f50-1f5c-43e7-826a-8fd45e2d6daf An Introduction to Reproducible Research is a 3-hour workshop aimed at introducing researchers to concepts, tools and practices to make their research workflows, data and results reproducible. The workshop challenges participants to use available tools and existing support to increase their research impact, quality and reproducibility through traditional and non-traditional outputs. 2022-10-11 09:00:00 UTC 2022-10-11 12:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop host_institution []
  • Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online

    11 October 2022

    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 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).** 2022-10-11 09:30:00 UTC 2022-10-11 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []
  • Learn to Program: Python at UNSW Online

    27 - 28 September 2022

    Learn to Program: Python at UNSW Online https://dresa.org.au/events/learn-to-program-python-at-unsw-online-7ae6e87c-4d3e-4850-a04c-d47ef535cc2b Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you'd expect of a modern programming language, and also a rich set of libraries for working with data. We teach using Jupyter notebooks, which allow program code, results, visualisations and documentation to be blended seamlessly. Perfect for sharing insights with others while producing reproducible research. Join us for this live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - Introduction to the JupyterLab interface for programming - Basic syntax and data types in Python - How to load external data into Python - Creating functions (FUNCTIONS) - Repeating actions and anylsing multiple data sets (LOOPS) - Making choices (IF STATEMENTS - CONDITIONALS) - Ways to visualise data in Python #### Prerequisites: No prior experience with programming needed to attend this course. We strongly recommend attending the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of previously delivered webinars can be found [here](https://intersect.org.au/training/webinars/). **For more information, please click [here](https://intersect.org.au/training/course/python101).** 2022-09-27 09:30:00 UTC 2022-09-28 12:30:00 UTC Intersect Australia Australia Australia UNSW training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online

    27 - 28 September 2022

    Introduction to Machine Learning using Python: Introduction & Linear Regression at UOA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-introduction-linear-regression-at-uoa-online 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).** 2022-09-27 09:30:00 UTC 2022-09-28 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []
  • Data Capture and Surveys with REDCap at LTU Online

    27 September 2022

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-db69a609-d9bc-4cae-b683-f3de30404c0a 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).** 2022-09-27 10:00:00 UTC 2022-09-27 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Classification at UniSA Online

    27 - 28 September 2022

    Introduction to Machine Learning using Python: Classification at UniSA Online https://dresa.org.au/events/introduction-to-machine-learning-using-python-classification-at-unisa-online Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries. #### You'll learn: - Comprehensive introduction to Machine Learning models and techniques such as 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).** 2022-09-27 13:00:00 UTC 2022-09-28 16:00:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []
  • Introduction to R for biologists

    28 September 2022

    North Melbourne, Australia

    Introduction to R for biologists https://dresa.org.au/events/introduction-to-r-for-biologists This workshop has been developed collaboratively by training specialists at Peter MacCallum Cancer Center and Melbourne Bioinformatics. This introduction to R and RStudio will provide beginners with experience with loading, manipulating and visualising biological data using the tidyverse collection of R packages. The example data used is publicly available RNA-seq data, therefore attendees will gain experience in the structure and appearance of RNA-seq data. 2022-09-28 10:00:00 UTC 2022-09-28 13:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of Melbourne bioinformatics-training@unimelb.edu.au [] beginnersLife scientists planning or running single cell RNAseq experiments (or mining public data), who want to perform their own analyses.Researchers and research students, or anyone who wants to learn intermediate statistical concepts to apply in R. 20 workshop host_institution RIntroductoryRNASeq
  • Data Entry and Processing in SPSS at UC Online

    29 - 30 September 2022

    Data Entry and Processing in SPSS at UC Online https://dresa.org.au/events/data-entry-and-processing-in-spss-at-uc-online-98ea1703-18fb-4677-af88-211451186b8c This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2022-09-29 09:30:00 UTC 2022-09-30 12:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Getting Started with NVivo for Mac at Western Sydney: Online

    29 September 2022

    Getting Started with NVivo for Mac at Western Sydney: Online https://dresa.org.au/events/getting-started-with-nvivo-for-mac-at-western-sydney-online-bafaf279-fd15-4e7a-86d1-dd5d382b63b5 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).** 2022-09-29 09:30:00 UTC 2022-09-29 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
  • Data Capture and Surveys with REDCap at LTU Online

    29 September 2022

    Data Capture and Surveys with REDCap at LTU Online https://dresa.org.au/events/data-capture-and-surveys-with-redcap-at-ltu-online-0c5f113e-e32d-4d2f-be91-4624b80e9cc4 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).** 2022-09-29 10:00:00 UTC 2022-09-29 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Network analysis of differentially-expressed genes using vissE and Cytoscape

    29 September 2022

    North Melbourne, Australia

    Network analysis of differentially-expressed genes using vissE and Cytoscape https://dresa.org.au/events/network-analysis-of-differentially-expressed-genes-using-visse-and-cytoscape In biological data, similarity between genes/proteins can be exploited to identify biological functions or pathways. For example, investigating pairwise protein-protein interactions can help us identify protein complexes that have related functions. Such analyses require pairwise interaction or similarity data to be represented as a biological network. Once generated, networks can be used to investigate various structural and topological characteristics to identify key entities in the network. A popular and powerful tool to visualise and analyse biological networks is Cytoscape. This workshop is in two parts. First, using an RNAseq data set from human cancer you will use the vissE tool analyse a list of differentially-expressed (DE) genes and generate a PPI network. In the second half you will be introduced to Cytoscape interface and learn how biological networks can be uploaded and analysed in Cytoscape. 2022-09-29 10:30:00 UTC 2022-09-29 15:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of MelbourneMelbourne Bioinformatics bioinformatics-training@unimelb.edu.au [] beginnersResearchers and research students, or anyone who wants to learn intermediate statistical concepts to apply in R. 20 workshop host_institution CytoscapevissEgene listsNetworks
  • Getting started with NVivo for Windows at UNE Online

    30 September 2022

    Getting started with NVivo for Windows at UNE Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-une-online Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in the one location makes, it's easy to see why NVivo is becoming the tool of choice for many researchers. NVivo allows researchers to simply organise and manage data from a variety of sources including surveys, interviews, articles, video, email, social media and web content, PDFs and images. Coding your data allows you to discover trends and compares themes as they emerge across different sources and data types. Using NVivo memos and visualisations combined with the ability to integrate with popular bibliographic tools you can get your research ready for publication sooner. #### You'll learn: - Create and organise a qualitative research project in NVivo - Import a range of data sources using NVivo's integrated tools - Code and classify your data - Format your data to take advantage of NVivo’s auto-coding ability - Use NVivo to discover new themes and trends in research - Visualise relationships and trends in your data #### Prerequisites: In order to participate, attendees must have a licensed copy of NVivo installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. This course is taught using NVivo 12 Pro for Windows and is not suitable for NVivo for Mac users. **For more information, please click [here](https://intersect.org.au/training/course/nvivo101).** 2022-09-30 09:30:00 UTC 2022-09-30 12:30:00 UTC Intersect Australia Australia Australia UNE training@intersect.org.au [] [] [] host_institution []
  • Unix Shell and Command Line Basics at UTS Online

    30 September 2022

    Unix Shell and Command Line Basics at UTS Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-uts-online-18e59a6f-4e60-43a6-82f6-d441e8c9e941 The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2022-09-30 10:00:00 UTC 2022-09-30 13:00:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Unix Shell and Command Line Basics at LTU Online

    30 September 2022

    Unix Shell and Command Line Basics at LTU Online https://dresa.org.au/events/unix-shell-and-command-line-basics-at-ltu-online-ddac198e-04d0-42b2-b604-85b8cbbe691a The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated. And it comes with a swag of handy tools that can be combined in powerful ways. Getting started is the hardest part, but our helpful instructors are there to demystify Unix as you get to work running programs and writing scripts on the command line. Every attendee is given a dedicated training environment for the duration of the workshop, with all software and data fully loaded and ready to run. We teach this course within a GNU/Linux environment. This is best characterised as a Unix-like environment. We teach how to run commands within the Bash Shell. The skills you'll learn at this course are generally transferable to other Unix environments. #### You'll learn: - Navigate and work with files and directories (folders) - Use a selection of essential tools - Combine data and tools to build a processing workflow - Automate repetitive analysis using the command line #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/unix101).** 2022-09-30 10:00:00 UTC 2022-09-30 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Introduction to Machine Learning using Python: Classification at UOA Online

    4 - 5 October 2022

    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 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).** 2022-10-04 09:30:00 UTC 2022-10-05 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []
  • Introduction to UNIX

    4 October 2022

    North Melbourne, Australia

    Introduction to UNIX https://dresa.org.au/events/introduction-to-unix-9a3165bd-34a3-4870-94e4-4c2e1f8b4d26 Knowledge of the Unix operating system is fundamental to the use of many popular bioinformatics command-line tools. Whether you choose to run your analyses locally or on an HPC system, knowing your way around a command-line interface is highly valuable. This workshop will introduce you to Unix concepts by way of a series of hands-on exercises. Completion of this workshop will provide the background knowledge required for other Melbourne Bioinformatics workshops that require command-line skills. 2022-10-04 10:00:00 UTC 2022-10-04 14:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of Melbourne bioinformatics-training@unimelb.edu.au [] beginners 20 workshop host_institution Unix
  • Longitudinal Trials with REDCap at LTU Online

    4 October 2022

    Longitudinal Trials with REDCap at LTU Online https://dresa.org.au/events/longitudinal-trials-with-redcap-at-ltu-online-fab74bbb-894b-4e69-8157-2498a9138206 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).** 2022-10-04 10:00:00 UTC 2022-10-04 13:00:00 UTC Intersect Australia Australia Australia LTU training@intersect.org.au [] [] [] host_institution []
  • Data Entry and Processing in SPSS at UC Online

    4 - 5 October 2022

    Data Entry and Processing in SPSS at UC Online https://dresa.org.au/events/data-entry-and-processing-in-spss-at-uc-online-2ad49709-9422-4151-b2b5-47e7e0ba5976 This hands-on training is designed to familiarize you with the interface and basic data processing functionalities in SPSS. We will examine several “must know” syntax commands that can help streamline data entry and processing. In addition, we will explore how to obtain descriptive statistics in SPSS and perform visualization. This workshop is recommended for researchers and postgraduate students who are new to SPSS or Statistics; or those simply looking for a refresher course before taking a deep dive into using SPSS, either to apply it to their research or to add it to their arsenal of eResearch skills. #### You'll learn: - Navigate the SPSS working environment - Prepare data files and define variables - Enter data in SPSS and Import data from Excel - Perform data screening - Compose SPSS Syntax for data processing - Obtain descriptive statistics, create graphs & assess normality - Manipulate and transform variables #### Prerequisites: In order to participate, attendees must have a licensed copy of SPSS installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/spss101).** 2022-10-04 13:30:00 UTC 2022-10-05 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Design and Analysis of Surveys 1: Best Practice

    5 October 2022

    Design and Analysis of Surveys 1: Best Practice https://dresa.org.au/events/design-and-analysis-of-surveys-1-best-practice This workshop is full of practical tips and guidelines on how to design, field and analyse standard surveys. Some of the topics considered will be: how to design a survey, line vs discrete scales, the effect of colour, optimal discrete/LIKERT scales, pros and cons of common analyses (e.g. linear and logistic regression) and optimal ways to export data. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 09:30:00 UTC 2022-10-05 11:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Design and Analysis of Surveys 1: Advanced Topics

    5 October 2022

    Design and Analysis of Surveys 1: Advanced Topics https://dresa.org.au/events/design-and-analysis-of-surveys-1-advanced-topics This workshop builds on the material in Surveys 1. It explores questionnaire validation and index creation using methods such as: Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) using Structural Equation Modelling (SEM), and Conjoint models such as Choice modelling. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 11:30:00 UTC 2022-10-05 13:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Design and Analysis of Surveys 2: Advanced Topics

    5 October 2022

    Design and Analysis of Surveys 2: Advanced Topics https://dresa.org.au/events/design-and-analysis-of-surveys-2-advanced-topics This workshop builds on the material in Surveys 1. It explores questionnaire validation and index creation using methods such as: Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) using Structural Equation Modelling (SEM), and Conjoint models such as Choice modelling. The material is software agnostic and can be applied in any software. This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Attendance options:** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person:** Choose the "In person" ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online:** Choose the "Online Zoom" ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date.  Sydney Informatics Hub - Please use your **University of Sydney email address** to register i.e. **@sydney.edu.au, @uni.sydney.edu.au,** etc - If you do not have a UniKey, please contact us to confirm your position after registration. - Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you! 2022-10-05 11:30:00 UTC 2022-10-05 13:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Multivariate Statistical Analysis 1: Dimension Reduction

    5 October 2022

    Multivariate Statistical Analysis 1: Dimension Reduction https://dresa.org.au/events/multivariate-statistical-analysis-1-dimension-reduction-5209a7a6-36ba-4a48-923d-58f236456361 **Multivariate Statistical Analysis 1: Dimension Reduction** In multivariate statistics we simultaneously model and estimate variability in more than one variable often in order to examine the relationship between variables. This workshop examines the key aspects of moving from univariate to multivariate analysis, and the situations and scenarios where multivariate analysis is typically applied. The focus will be on practical application of concepts through examples. **Topics covered will include:** - Motivations for undertaking multivariate analysis - Statistical principles for multivariate analysis - Dimension reduction techniques including principal components analysis (PCA), factor analysis (FA), correspondence analysis (CA) and non-metric multidimensional scaling (nMDS) This is just one workshop from a modular training programme made up of 1.5 hour workshops, each focusing on a single statistical method offered by Statistical Consulting within the Sydney Informatics Hub. Statistical Workflows giving practical step-by-step instructions applicable in any software are used and include experimental design, exploratory analysis, modelling, assumption testing, model interpretation and presentation of results. Researchers are encouraged to design a custom programme tailored to their research needs. **Pre-requisites** Prior experience with statistical modelling is assumed, as the basics of regression modelling will not be covered. Please consider attending Linear Models 1 and/or Linear Models 2 workshops to come up to speed beforehand. Note that this workshop does not require knowledge of or use of specific statistics software. The analysis methods may be performed using a wide range of commonly available software. **Attendance options** You will get the most out of this session by attending in person. This way allows you to interact with the presenters, ask questions directly, and catch up after the session. Please only choose online if circumstances prevent you from attending campus. **In person**: Choose the _**In person**_ ticket option. University rules governing COVID related requirements will apply in the venue. In the event that in person delivery is not possible, you will be provided with the Zoom link for remote attendance. **Online**: Choose the _**Online Zoom**_ ticket option. It is recommended to have a dual monitor setup to view and participate remotely in the session. Registered attendees will receive a link to the Zoom event closer to the date. Sydney Informatics Hub - Open to: Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey) - Please use your University of Sydney email address to register i.e. @sydney.edu.au, @uni.sydney.edu.au, etc - If you do not have a UniKey, please contact us to confirm your position after registration. **Registrations from open web email clients (@gmail.com, @hotmail.com etc) will AUTOMATICALLY be cancelled, without us contacting you!!!** 2022-10-05 14:00:00 UTC 2022-10-05 15:30:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Introduction to Machine Learning using R: Introduction & Linear Regression at UniSA Online

    6 - 7 October 2022

    Introduction to Machine Learning using R: Introduction & Linear Regression at UniSA Online https://dresa.org.au/events/introduction-to-machine-learning-using-r-introduction-linear-regression-at-unisa-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).** 2022-10-06 09:30:00 UTC 2022-10-07 12:30:00 UTC Intersect Australia Australia Australia UniSA training@intersect.org.au [] [] [] host_institution []
  • QIIME2 analysis of 16S rRNA

    6 October 2022

    North Melbourne, Australia

    QIIME2 analysis of 16S rRNA https://dresa.org.au/events/qiime2-analysis-of-16s-rrna This workshop will give you an introduction to the QIIME2 analysis platform using 16S rRNA amplicon data from coral-associated bacteria. 2022-10-06 10:00:00 UTC 2022-10-06 14:00:00 UTC Melbourne Bioinformatics 21 Bedford Street, North Melbourne, Australia 21 Bedford Street North Melbourne Australia 3051 University of MelbourneMelbourne Bioinformatics bioinformatics-training@unimelb.edu.au [] researcherspeople with command line experience 20 workshop host_institution Qiime2Metabarcoding
  • Intro to REDCap (webinar)

    6 October 2022

    Intro to REDCap (webinar) https://dresa.org.au/events/intro-to-redcap-webinar Research Electronic Data Capture (REDCap) is a secure web-based database application maintained by the University of Sydney. It is ideal for collecting and managing participant data and administering online surveys, with features supporting longitudinal data collection, complex team workflows and exports to a range of statistical analysis programs. **In "Intro to REDCap", we will cover:** - How to build a simple data entry project - How to collect data - How to add users/collaborators - How to export data Please note we will **not cover surveys**, as these are covered separately in our "Surveys in REDCap" training session. **Target audience:** Students and staff at the University of Sydney who need to collect electronic data or responses from participants into a structured database. **Open to:** Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey). If you do not have a UniKey, please contact us to confirm your position after registration. Please use your University of Sydney email address to register (e.g. first.last@sydney.edu.au, abcd1234@uni.sydney.edu.au) **Accessing the webinar:** Your confirmation **email from Eventbrite** will contain a button which will provide the details to access the Zoom webinar **For more information:** digital.research@sydney.edu.au Sydney Informatics Hub offers a broad range of training to researchers at the University. Please see our [training site](https://sydney.edu.au/research/facilities/sydney-informatics-hub/workshops-and-training.html)for more information. 2022-10-06 10:00:00 UTC 2022-10-06 12:00:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []
  • Excel for Researchers at Deakin Online

    6 - 7 October 2022

    Excel for Researchers at Deakin Online https://dresa.org.au/events/excel-for-researchers-at-deakin-online-bab9bfd3-9f50-4b1a-bd93-612966314ddd Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data. #### You'll learn: - 'Clean up’ messy research data - Organise, format and name your data - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING) - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP) - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS) - Handy tips to speed up your work #### Prerequisites: In order to participate, attendees must have a licensed copy of Microsoft Excel installed on their computer. Speak to your local university IT or Research Office for assistance in obtaining a license and installing the software. **For more information, please click [here](https://intersect.org.au/training/course/excel101).** 2022-10-06 13:00:00 UTC 2022-10-07 16:00:00 UTC Intersect Australia Australia Australia Deakin training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at UTS Online

    6 October 2022

    Getting started with NVivo for Windows at UTS Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uts-online-b28faf2f-9fd5-4807-b81e-314757189cfc 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).** 2022-10-06 13:30:00 UTC 2022-10-06 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Version Control with Git at UC Online

    6 October 2022

    Version Control with Git at UC Online https://dresa.org.au/events/version-control-with-git-at-uc-online Have you mistakenly overwritten programs or data and want to learn techniques to avoid repeating the loss? Version control systems are one of the most powerful tools available for avoiding data loss and enabling reproducible research. While the learning curve can be steep, our trainers are there to answer all your questions while you gain hands on experience in using Git, one of the most popular version control systems available. Join us for this workshop where we cover the fundamentals of version control using the researcher-focused training modules from the highly regarded Software Carpentry Foundation. #### You'll learn: - keep versions of data, scripts, and other files - examine commit logs to find which files were changed when - restore earlier versions of files - compare changes between versions of a file - push your versioned files to a remote location, for backup and to facilitate collaboration #### Prerequisites: The course has no prerequisites. **For more information, please click [here](https://intersect.org.au/training/course/git101).** 2022-10-06 13:30:00 UTC 2022-10-06 16:30:00 UTC Intersect Australia Australia Australia UC training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at Western Sydney: Online

    7 October 2022

    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-553d211b-e146-4d09-9cd0-e8deed4614fb 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).** 2022-10-07 09:30:00 UTC 2022-10-07 12:30:00 UTC Intersect Australia Australia Australia WSU training@intersect.org.au [] [] [] host_institution []
  • Getting started with NVivo for Windows at UTS Online

    7 October 2022

    Getting started with NVivo for Windows at UTS Online https://dresa.org.au/events/getting-started-with-nvivo-for-windows-at-uts-online-3b35237e-2329-460c-b21d-edb3e4005185 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).** 2022-10-07 13:30:00 UTC 2022-10-07 16:30:00 UTC Intersect Australia Australia Australia UTS training@intersect.org.au [] [] [] host_institution []
  • Introduction to Reproducible Research

    11 October 2022

    Introduction to Reproducible Research https://dresa.org.au/events/introduction-to-reproducible-research-40989f50-1f5c-43e7-826a-8fd45e2d6daf An Introduction to Reproducible Research is a 3-hour workshop aimed at introducing researchers to concepts, tools and practices to make their research workflows, data and results reproducible. The workshop challenges participants to use available tools and existing support to increase their research impact, quality and reproducibility through traditional and non-traditional outputs. 2022-10-11 09:00:00 UTC 2022-10-11 12:00:00 UTC QCIF QCIF training@qcif.edu.au [] [] workshop host_institution []
  • Introduction to Machine Learning using Python: SVM & Unsupervised Learning at UOA Online

    11 October 2022

    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 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).** 2022-10-11 09:30:00 UTC 2022-10-11 12:30:00 UTC Intersect Australia Australia Australia UOA training@intersect.org.au [] [] [] host_institution []

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