The basics of GenAI: theory and practice
Full-day training for PhD students, consisting of a theoretical lecture followed by a hands-on practical workshop. Designed to provide doctoral students with a deeper insight into the fundamental workings of Large Language Models, which form the basis of many generative AI applications such as ChatGPT.
NEW DATE!
Practical information:
Want to register?
- Price: free
You need to be a PhD student at a Flemish university to enroll
Bring your laptop (fully charged)
Georganiseerd door:
Leertraject
After following this course, you'll have gained:
- Fundamental insight into the inner workings of Large Language Models
- Logical understanding of specific LLM phenomena such as ‘hallucinations’
- More concrete knowledge on how LLMs are trained and further refined
- Best practices for using Generative AI to support academic research
- Concrete examples of different parts of academic research workflows which involve using LLMs
- Hands-on experience with data conversion and code generation using LLMs
Programme
Understanding the basics of Generative AI
This 2-hour lecture outlines the fundamental algorithmic structure of Large Language Models to clarify both the impressive capacities and remaining limitations of these models. It highlights why small changes in prompts can cause substantial differences in model behavior, and how LLMs can be used both with randomness or deterministically.
Best practices for using Generative AI for academic research
This workshop utilizes the insights of the morning lecture to teach best practices for using Generative AI to support academic research. Going beyond prompt engineering, it highlights effective workflows which consider both the basic limitations of LLMs as well as their versatile output formats.
Practical examples include data conversion, code generation, and various Natural Language Processing tasks such as summarization, literature review, and academic rewriting.
Teacher / speaker
Pieter Fivez
Pieter Fivez holds a PhD in Linguistics from the University of Antwerp, focusing on machine learning of semantic representations of biomedical text. He currently works as a postdoctoral researcher at the University of Antwerp, where he coordinates the Antwerp Text Mining Centre (TEXTUA).
Prompt. Think. Defend. Data and AI for PhD Students
PhD student? This lesson series guides you through data and AI: from introductory courses to in-depth courses on various subtopics. VAIA selected these courses specifically for PhD students, in close collaboration with all the Flemish universities, doctoral schools and a various lectures. Register for the mailer for updates about the programme!
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