This training offered a structured introduction to generative artificial intelligence for a technical audience involved in the development of digital educational tools. Over the course of three and a half hours, participants explored how these technologies work, their real-world use cases, as well as the associated regulatory and ethical challenges. The program combined theoretical insights, practical demonstrations, and experience sharing.
Objectives of the training :
By the end of the training, participants will be able to:
Targeted Skills and Learning Outcomes :
Participants will develop the following skills:
Schedule | Theme & Activity
9:00 – 9:15 | Welcome & Introduction: Presentation of objectives, speakers, and brief roundtable.
Topic: General concepts of generative AI
9:15 – 9:45 | Overview of Generative Models: Introduction to LLMs, open-source vs. proprietary models, fine-tuning, embeddings.
9:45 – 10:30 | RAG & Agentic Systems – Retrieval-Augmented Generation: How RAG architectures work.
10:30 – 10:45 | Coffee Break
10:45 – 11:30 | Python for Generative AI: Presentation of key libraries – Hugging Face (transformers, datasets), LangChain.
11:30 – 12:00 | Ethical & GDPR Issues: Key principles – data storage, usage rights, transparency, bias, and data protection.
12:00 – 12:30 | Conclusion, Discussion & Feedback: Summary of key points, Q&A, distribution of additional resources (links, MOOCs).
The training was offered to the following audience:
Software engineers and technicians involved in educational projects
Technical professionals interested in understanding generative AI within the context of higher education