Hands-on workshop
Agentic coding with GitHub Copilot
3 dec. 2026 09:30 - 17:00
In this hands-on workshop, you'll learn how to move beyond chat-based coding and design structured, agentic coding workflows. Using GitHub Copilot, you will learn to write effective prompts, leverage LLMs for multi-file coding tasks, and design workflows that plan, act, and iterate safely.
Praktische info:
3 dec. 2026 09:30 - 17:00
8 uur
Technologiepark 75, 9052 Zwijnaarde, Belgium
Engels
Doelgroep: PhD, Postdoc, staff scientist, group leader or expert, technical support etc
Inschrijven?
- Voorwaarden: Basic programming experience (Python or other) Familiarity with chat-based LLM tools Familiarity with Git is advisable GitHub account (and license)
- Prijs: €100, €500
georganiseerd door:
Leertraject
The course features a mix of explanations, live demonstrations, and hands-on exercises, giving you the opportunity to apply LLMs to real-world coding challenges. You’ll also explore how to evaluate agent outputs, implement guardrails, and address important risks and governance issues. By the end of the training, you'll be able to use LLMs for structured coding tasks, design robust agentic workflows, and enhance productivity in your own projects.
Learning outcomes
- Explain key concepts and terminology related to agentic coding (agents, planning loops, tools, guardrails).
- Describe the agent loop (goal → plan → act → observe → revise) and its implications for software development.
- Summarize common failure modes and risks of coding agents.
- Write effective prompts and task descriptions that guide agent behavior.
- Critically review agent-generated code for correctness, maintainability, and security.
- Design an end-to-end agentic workflow for a realistic coding scenario.
- Produce a reusable prompt or workflow template that can be applied in your own projects
Lesgever/spreker
Jolan Heyse
Jolan Heyse is a trainer at VIB specializing in artificial intelligence and data science for life sciences. He holds a master's degree and a PhD in Biomedical Engineering from Ghent University, where his research focused on applying AI to EEG-based epilepsy diagnosis. Before joining VIB, Jolan worked as a data scientist at AZ Delta, developing AI applications for healthcare. His expertise includes machine learning, biomedical signal processing, Large Language Models (LLMs), and translating complex algorithms into practical tools for researchers. At VIB, he designs and delivers training programs to help scientists with data-driven methods.
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