A hands on introduction to Large Language Models like Bing Chat and ChatGPT
Event run 7 June at the MQ Incubator. Event description:
A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI."
These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of...
Keywords: Large Language Model, ChatGPT
A hands on introduction to Large Language Models like Bing Chat and ChatGPT
https://osf.io/rd24y/
https://dresa.org.au/materials/a-hands-on-introduction-to-large-language-models-like-bing-chat-and-chatgpt
Event run 7 June at the MQ Incubator. Event description:
A two-hour hands-on workshop giving a brief history of the last 4 months of development of "Generative AI."
These tools, these Large Language Models, offer present promise and peril -- disruption -- to ways of working and of learning. Outside the "hype," these tools are "calculators for words" and allow the same manipulation and reflection of a user's words as a calculator offers for a user's numbers.
The workshop will guide users into using various free and paid tools, and the effective use of Large Language Models through chain of thought prompting.
Remember: a LLM is "Always confident and usually correct."
OSF Description (LLM generated):
This two-hour workshop provides a comprehensive introduction to the world of Large Language Models (LLMs), focusing on the recent advancements in Generative AI. Participants will gain insights into the development and functionality of prominent LLMs such as Bing Chat and ChatGPT. The workshop will delve into the concept of LLMs as "calculators for words," highlighting their potential to revolutionize ways of working and learning.
The session will explore the principles of Prompt Engineering and Transactional Prompting, demonstrating how consistent prompts can yield reliable and reproducible results. Participants will also learn about the practical applications of LLMs, including editing and proofreading papers, generating technical documentation, recipe ideation, and more.
The workshop emphasizes the importance of understanding the terms of use and the responsibilities that come with using these powerful AI tools. By the end of the session, participants will be equipped with the knowledge and skills to effectively use LLMs in various contexts, guided by the mantra that a LLM is "Always confident and usually correct."
Brian Ballsun-Stanton (brian.ballsun-stanton@mq.edu.au)
Brian Ballsun-Stanton
Large Language Model, ChatGPT
researcher
Introduction to REDCap at Griffith University
This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.
Keywords: REDCap, survey instruments
Resource type: tutorial
Introduction to REDCap at Griffith University
https://griffithunilibrary.github.io/redcap-intro/
https://dresa.org.au/materials/introduction-to-redcap-at-griffith-university
This site is designed as a companion to Griffith Library’s Research Data Capture workshops. It can also be treated as a standalone, self-paced tutorial for learning to use REDCap (Research Electronic Data Capture) a secure web application for building and managing online surveys and databases.
y.banens@griffith.edu.au
Yuri Banens
REDCap, survey instruments
mbr
phd
ecr
researcher
support
Introduction to text mining and analysis
In this self-paced workshop you will learn steps to:
- Build data sets: find where and how to gather textual data for your corpus or data set.
- Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis
- Analyse data: identify different...
Keywords: textual training materials
Resource type: tutorial
Introduction to text mining and analysis
https://griffithunilibrary.github.io/intro-text-mining-analysis/
https://dresa.org.au/materials/introduction-to-text-mining-and-analysis
In this self-paced workshop you will learn steps to:
- Build data sets: find where and how to gather textual data for your corpus or data set.
- Prepare data for analysis: explore useful processes and tools to prepare and clean textual data for analysis
- Analyse data: identify different types of analysis used to interrogate content and uncover new insights
s.stapleton@griffith.edu.au; y.banens@griffith.edu.au;
Yuri Banens
Sharron Stapleton
Ben McRae
textual training materials
mbr
phd
ecr
researcher
support
Introducing Computational Thinking
This workshop is for researchers at all career stages who want to understand the uses and the building blocks of computational thinking. This skill is useful for all kinds of problem solving, whether in real life or in computing.
The workshop will not teach computer programming per se. Instead...
Keywords: computational skills, data skills
Resource type: tutorial
Introducing Computational Thinking
https://griffithunilibrary.github.io/intro-computational-thinking/
https://dresa.org.au/materials/introducing-computational-thinking
This workshop is for researchers at all career stages who want to understand the uses and the building blocks of computational thinking. This skill is useful for all kinds of problem solving, whether in real life or in computing.
The workshop will not teach computer programming per se. Instead it will cover the thought processes involved should you want to learn to program.
s.stapleton@griffith.edu.au
Belinda Weaver
computational skills, data skills
The Living Book of Digital Skills
The Living Book of Digital Skills (You never knew you needed until now) is a living, open source online guide to 'modern not-quite-technical computer skills' for researchers and the broader academic community.
A collaboration between Australia's Academic Research Network (AARNet) and the...
Keywords: digital skills, digital dexterity, community, open source
Resource type: guide
The Living Book of Digital Skills
https://aarnet.gitbook.io/digital-skills-gitbook-1/
https://dresa.org.au/materials/the-living-book-of-digital-skills
*The Living Book of Digital Skills (You never knew you needed until now)* is a living, open source online guide to 'modern not-quite-technical computer skills' for researchers and the broader academic community.
A collaboration between Australia's Academic Research Network (AARNet) and the Council of Australian Librarians (CAUL), this book is the creation of the CAUL Digital Dexterity Champions and their communities.
**Contributing to the Digital Skills GitBook**
The Digital Skills GitBook is an open source project and like many projects on GitHub we welcome your contributions.
If you have knowledge or expertise on one of our [requested topics](https://aarnet.gitbook.io/digital-skills-gitbook-1/requested-articles), we would love you to write an article for the book. Please let us know what you'd like to write about via our [contributor form](https://github.com/AARNet/Digital-Skills-GitBook/issues/new?assignees=sarasrking&labels=contributors&template=contributor-form.yml&title=Contributor+form%3A+).
There are other ways to contribute too. For example, you might:
* have a great idea for a new topic to be included in one of our chapters (make a new page)
* notice some information that’s out-of-date or that could be explained better (edit a page)
* come across something in the GitBook that’s not working as it should be (submit an issue)
Sara King - sara.king@aarnet.edu.au
Sara King
Miah de Francesch
Emma Chapman
Katie Mills
Ruth Cameron
digital skills, digital dexterity, community, open source
ugrad
masters
mbr
phd
ecr
researcher
support
Research Data Management (RDM) Online Orientation Module (Macquarie University)
This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata,...
Keywords: research data, data management, FAIR data, training
Resource type: quiz, activity, other
Research Data Management (RDM) Online Orientation Module (Macquarie University)
https://rise.articulate.com/share/-AWqSPaEI_jTbHwzQHdmQ43R50edrCl0
https://dresa.org.au/materials/macquarie-university-research-data-management-rdm-online
This is a self-paced, guided orientation to the essential elements of Research Data Management. It is available for others to use and modify.
The course introduces the following topics: data policies, data sensitivity, data management planning, storage and security, organisation and metadata, benefits of data sharing, licensing, repositories, and best practice including the FAIR principles.
Embedded activities and examples help extend learner experience and awareness.
The course was designed to assist research students and early career researchers in complying with policies and legislative requirements, understand safe data practices, raise awareness of the benefits of data curation and data sharing (efficiency and impact) and equip them with the required knowledge to plan their data management early in their projects.
This course is divided into four sections
1. Crawl - What is Research Data and why care for it? Policy and legislative requirements. The Research Data Life-cycle. Data Management Planning (~30 mins)
2. Walk - Data sensitivity, identifiability, storage, and security (~60 mins)
3. Run - Record keeping, data retention, file naming, folder structures, version control, metadata, data sharing, open data, licences, data repositories, data citation, and ethics (~75 mins)
4. Jump - Best practice FAIR data principles (~45 mins)
5. Fight - Review - a quiz designed to review and reinforce knowledge (~15 mins)
https://rise.articulate.com/share/-AWqSPaEI_jTbHwzQHdmQ43R50edrCl0 *
*Password: "FAIR"
*Password: "FAIR"
Any queries or suggestions for course improvement can be directed to the Macquarie University Research Integrity Team: Dr Paul Sou (paul.sou@mq.edu.au) or Dr Shannon Smith (shannon.smith@mq.edu.au). Scorm files can be made available upon request.
Macquarie University
Queensland University of Technology
Shannon Smith
Jennifer Rowland
Mark Hooper
Paul Sou
Vladimir Bubalo
Brian Ballsun-Stanton
research data, data management, FAIR data, training