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Authors: Williams, Jason (orcid: 000...  or Zhang, Eden (orcid: 0000-00... 

WORKSHOP: Introduction to Machine Learning in R - from data to knowledge

This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Machine Learning in R - from data to knowledge’. This workshop took place over one, 4 hour sessions on 09 December 2024.
Event description
With the rise in high-throughput sequencing...

Keywords: Bioinformatics, Machine Learning

WORKSHOP: Introduction to Machine Learning in R - from data to knowledge https://dresa.org.au/materials/workshop-introduction-to-machine-learning-in-r-from-data-to-knowledge This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Machine Learning in R - from data to knowledge’. This workshop took place over one, 4 hour sessions on 09 December 2024. Event description With the rise in high-throughput sequencing technologies, the volume of omics data has grown exponentially. A major issue is to mine useful knowledge from these heterogeneous collections of data. The analysis of complex high-volume data is not trivial and classical tools cannot be used to explore their full potential. Machine Learning (ML), a discipline in which computers perform automated learning without being programmed explicitly and assist humans to make sense of large and complex data sets, can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of bioinformatics. This hands-on workshop will introduce participants to the ML taxonomy and the applications of common ML algorithms to health data. The workshop will cover the foundational concepts and common methods being used to analyse omics data sets by providing a practical context through the use of basic but widely used R libraries. Participants will acquire an understanding of the standard ML processes, as well as the practical skills in applying them on familiar problems and publicly available real-world data sets. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Lead trainers: Dr Fotis Psomopoulos, Senior Researcher,  Institute of Applied Biosciences (INAB), Center for Research and Technology Hellas (CERTH) Facilitators: Dr Giorgia Mori, Australian BioCommons Dr Eden Zhang, Sydney Informatics Hub Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) Infrastructure provision: Uwe Winter, Australian BioCommons Host: Dr. Giorgia Mori, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Files and materials shared elsewhere: Training materials webpage Data and documentation     Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Machine Learning
WEBINAR: Effective, inclusive, and scalable training in the life sciences, clinical education and beyond

This record includes training materials associated with the Australian BioCommons/Melbourne Genomics webinar ‘Effective, inclusive, and scalable training in the life sciences, clinical education and beyond’. This webinar took place on 4 November 2022.

Event description 

Scientists and educators...

Keywords: Short-format training, Clinical education, Continuing education, Professional development, Training, Lifelong learning, Pedagogy

WEBINAR: Effective, inclusive, and scalable training in the life sciences, clinical education and beyond https://dresa.org.au/materials/webinar-effective-inclusive-and-scalable-training-in-the-life-sciences-clinical-education-and-beyond-52c113ff-573c-4ae8-a3f0-482c86f1818a This record includes training materials associated with the Australian BioCommons/Melbourne Genomics webinar ‘Effective, inclusive, and scalable training in the life sciences, clinical education and beyond’. This webinar took place on 4 November 2022. Event description  Scientists and educators working in the life sciences must continuously acquire new knowledge and skills to stay up-to-date with the latest methods, technologies and research. Short-format training, such as webinars, workshops and bootcamps, are popular ways of quickly learning about new topics and gaining new skills. As trainers and educators, how can we ensure that short-format training is effective and inclusive for all? How can we ensure that our learners are equipped to continue learning and applying their new skills once they return to their day jobs? And how can we do this in a way that is scalable and sustainable? The Bicycle Principles assemble education theory and community experience into a framework for improving short-format training so that it is effective, inclusive and scalable. Over 30 international experts, including colleagues from the Australian BioCommons, Melbourne Genomics and other Australian and New Zealand organisations, helped develop the principles and an associated set of recommendations. Jason Williams, Assistant Director, DNA Learning Center, Cold Spring Harbor Laboratory - a leading genomics and bioinformatics educator and project lead, joins us to discuss the Principles and how they can be applied to achieve scalable and sustainable training in a range of Australian settings. This webinar is co-hosted by Australian BioCommons and Melbourne Genomics Training Materials Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. WILLIAMS-Jason_aus-biocommons_nov-2022 (PDF): A PDF copy of the slides presented during the webinar. Materials shared elsewhere:   A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/18dub7jGeQ8 Melissa Burke (melissa@biocommons.org.au) Short-format training, Clinical education, Continuing education, Professional development, Training, Lifelong learning, Pedagogy
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

 

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists-81aa00db-63ad-4962-a7ac-b885bf9f676b This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.   Event description Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: Spreadsheets, organising data and first steps with R Manipulating and analysing data with dplyr Data visualisation Summarized experiments and getting started with Bioconductor   This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Schedule (PDF): A breakdown of the topics and timings for the workshop Recommended resources (PDF): A list of resources recommended by trainers and participants Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere:   This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
Professionalizing Training - Origin Stories for the Modern Researcher

Keynote Presentation for the ARDC Skills Summit 2023

This keynote presentation provides a brief outline of Jason William’s experience and an overview of the training initiatives he has been involved in. His presentation looks at what makes a good researcher and provokes thinking about modern...

Keywords: research, training, skills, superheroes, formal, career, change, workshops, milestones, community, principles, bicycle principles, professionalizing, training material

Professionalizing Training - Origin Stories for the Modern Researcher https://dresa.org.au/materials/professionalizing-training-origin-stories-for-the-modern-researcher-0198d9cf-9d8f-467e-8031-4d3a3536af63 Keynote Presentation for the ARDC Skills Summit 2023 This keynote presentation provides a brief outline of Jason William’s experience and an overview of the training initiatives he has been involved in. His presentation looks at what makes a good researcher and provokes thinking about modern researchers and the need for them to get serious bout career-spanning training. Jason also provides an overview of the Bike Principles and focuses on the first Bike Principles recommendation - Professionalize the training of short-format training instructors and instructional designers. contact@ardc.edu.au research, training, skills, superheroes, formal, career, change, workshops, milestones, community, principles, bicycle principles, professionalizing, training material
Exploratory Data Analysis

This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 1: https://youtu.be/dMwHFhKWRRI

Module 3:...

Keywords: Data analysis, training material

Exploratory Data Analysis https://dresa.org.au/materials/exploratory-data-analysis This is the second of three modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 1**: [https://youtu.be/dMwHFhKWRRI](https://youtu.be/dMwHFhKWRRI) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Mori, Giorgia (orcid: 0000-0003-3469-5632) Data analysis, training material
Fundamentals of Machine Learning

This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH).

Module 2: https://youtu.be/HVAFflj2PS0
Module 3:...

Keywords: Machine Learning, training material

Fundamentals of Machine Learning https://dresa.org.au/materials/fundamentals-of-machine-learning This is the first of four modules in our exciting new machine learning workshop series by the Sydney Informatics Hub (SIH). **Module 2**: [https://youtu.be/HVAFflj2PS0](https://youtu.be/HVAFflj2PS0) **Module 3**: [https://github.com/Sydney-Informatics-Hub/Module3R](https://github.com/Sydney-Informatics-Hub/Module3R) *The Sydney Informatics Hub is a Core Research Facility at The University of Sydney, enabling excellence in research* [https://sydney.edu.au/informatics-hub](https://sydney.edu.au/informatics-hub) sih.training@sydney.edu.au Machine Learning, training material