9th-11th-13th February 2026

This course introduces participants to coding with large language models (LLMs), focusing on developing interactive web applications using Shiny in R. Participants will learn the fundamentals of LLMs, their limitations, and how to apply them effectively in coding workflows.

After a brief introduction to R and Shiny apps, the course emphasizes using LLMs and coding agents to develop, improve, and debug Shiny apps. Hands-on examples also introduce modern software development tools such as GitHub, Visual Studio Code (VS Code), Docker containers, and OpenAI’s Codex.

This course is aimed at biologists, data scientists, statisticians, bioinformaticians, and other practitioners interested in coding with AI. Participants should have some experience with R programming. Prior experience with Shiny is not required, but a willingness to learn new tools (GitHub, VS Code, Docker, Codex) is essential.

The course takes a progressive approach to software development and includes a mix of lectures and practical exercises.

By the end of the course, participants will be able to:

1. Understand the fundamentals of LLMs and their limitations

2. Use LLMs effectively in coding

3. Use LLM-based coding agents (e.g., Codex) effectively

4. Understand the basics of Shiny apps and design principles

5. Utilize modern software development tools for coding

Day 1 - Februarý 9th – Classes from 2–6 PM CET
Session 1: Introduction to LLMs

• Fundamentals of LLMs, applications, and limitations

• Prompt engineering

• Reasoning models, deep research, and agent modes

• Overview of models and providers

Session 2: Introduction to Shiny Apps

• Installing R locally or using Posit.cloud

• Basics of Shiny apps

• UI/UX design best practices

• Shiny modules and app maintainability

• Publishing Shiny apps

Day 2 – February 11th - Classes from 2–6 PM CET
Session 3: Version Control with GitHub

• Creating GitHub accounts

• Installing GitHub Desktop

• Coding with GitHub and LLMs

Session 4: Coding Strategies with LLMs

• Using ChatGPT and other LLMs to develop Shiny apps

• Being skeptical and always reviewing code

• Iterative refinement

• Self-reflection

• Plan, execute, review

Day 3 – February 13th-  Classes from 2–6 PM CET
Session 5: Introduction to Codex and Development Tools

• Installing Visual Studio Code (VS Code)

• Docker Desktop installation

• Running VS Code in containers

• Introduction to OpenAI’s Codex

Session 6: Effective Use of Coding Agents

• Coding workflows

• Strategies for using coding agents

• Lessons learned from real-world applications

1- AI for Genomics - ONLINE, 7-9 April

2 - Beyond Beginner R - ONLINE, 1-4 June

3 - Introduction to R Shiny - ONLINE, 9-10 June