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Good practice in research software development in the age of AI

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Good practice in research software development in the age of AI

Organiser (s)
Kyro Hartzenberg

Kyro Hartzenberg
Events details
Location: 

Zoom

Dates:

 24 November 2026 | 3 December 2026

Good practice in research software development in the age of AI

Event banner for AI series which includes Institute for Research Software logo and keyboard

The Institute for Research Software is running a series on Good practice in research software development in the age of AI.

This series provides researchers with accessible, practical training and resources to build understanding of artificial intelligence and develop skills to use AI tools effectively and responsibly in research. 

Taking place from 24 November to 3 December, this series will feature a variety of formats, including presentations from experts in the field, a panel discussion, training courses and blog posts, offering diverse opportunities to explore AI, its applications in research software, and good practice.

The training courses cater for a range of experience, from beginners with no coding background to researchers looking to integrate AI into established software development workflows. Through hands-on activities, participants will explore AI concepts, use AI to write, debug and understand code, and apply AI tools to plan and develop research software, while considering important issues around reliability, security, ethics and good software development practice.

Registration opens on 26 October via Eventbrite. 

Schedule & Registration

Below, you can find an overview of the schedule for the series. Please click on the session title to register via Eventbrite from 26 October.

Week 1 (24 - 26 November)

Date
Time
Information & register
Tuesday 24 November10:00 - 13:00AI Fundamentals for Researchers 
Tuesday 24 November14:00 - 17:00AI in Research: Ethical, Green, Data and Cognitive Considerations
Thursday 26 November09:30 - 13:00Coding with AI: Opportunities and Responsibilities for Researchers 

Week 2 (1 - 3 December)

Date
Time
Information & register
Tuesday 1 December09:30 - 16:30Developing Research Software with AI Tools (includes IDE intro) - Intermediate
Thursday 3 December09:30 - 16:30Advanced Research Software Development using AI 

Blog posts

In addition to the live sessions, there will also be a collection of blog posts published in the lead up to the series:

Date
Blog Post
Author
Monday 16 NovemberBlog post: AI & Green ConsiderationsKirsty Pringle
Tuesday 17 NovemberBlog post: AI & Data GovernanceKamilla Kopec-Harding
Wednesday 18 NovemberBlog post: AI & Cognitive OffloadingAnna-Stiina Wallinheimo

Session Descriptions

Below, you can find the descriptions and pre-requisites of the live sessions.

Tuesday 24 November

A beginner-level introduction to the landscape of Artificial Intelligence (AI) techniques. This course will help researchers build a foundational understanding of key areas within AI, including machine learning, deep learning, and large language models (LLMs) including what they are, how they work, and how they relate to one another within the broader AI ecosystem. Designed for researchers with little or no prior knowledge of AI, this course provides clear, accessible explanations without requiring any coding or statistics experience.

Tuesday 24 November

TBC

Thursday 26 November

A practical introduction to using AI to support coding in research. This course will help researchers understand how to use AI to help them write code effectively and responsibly. This course is designed for researchers with little to no experience coding. The course provides clear, hands-on guidance for using AI to write, debug, and understand code, while addressing key ethical, security, and reliability considerations in research contexts.

Tuesday 1 December

An intermediate-level course on integrating Artificial Intelligence (AI) tools into research software development. Building on foundational knowledge of large language models and AI coding assistants, this course focuses on using these tools effectively within integrated development environments. Researchers will develop practical skills to enhance productivity, improve code quality, and apply AI responsibly in real-world research projects.

Pre-requisites:

  • You have a basic knowledge of programming in Python (using variables, lists, conditional statements, functions and importing external libraries)
  • You have previously written Python scripts or
  •  iPython/Jupyter notebooks to accomplish tasks in your domain of work

Thursday 3 December

An advanced-level practical course on integrating Artificial Intelligence (AI) tools into research software development. This course explores task-based and process-based methods of using AI within the software development lifecycle while maintaining good software development practices. This course is for you if you have used GitHub Copilot in the past to improve your existing code, but would like to explore it further to plan and develop software from scratch using agents based on a defined set of project requirements.

Pre-requisites: 

  • You have a basic knowledge of programming in Python (using variables, lists, conditional statements, functions and importing external libraries)
  • You have previously written Python scripts or iPython/Jupyter notebooks to accomplish tasks in your domain of work
  • You have previously used Microsoft Visual Studio Code to develop code in any language (opening workspaces, editing files, installing extensions)
  • You have previously used GitHub Copilot to obtain suggestions to improve your code.
  • It is also helpful but not necessary to have some basic knowledge of Git version control (cloning repositories, making commits, pushing to a remote repository).
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