AI & ML

The architecture behind modern AI: how the transformer and its attention mechanism power LLMs, translation and today's generative models.

Where AI bias comes from and how to address it — a practical look at fairness, transparency and responsible AI in real-world projects.

A plain-English guide to AI agents — how they plan, use tools and act autonomously to complete multi-step tasks beyond simple chatbots.

What generative AI really is: how models create text, images and audio, what they can and can't do, and where the technology is headed.

How reinforcement learning works — agents, rewards and policies — and how trial-and-error training drives game-playing AI and robotics.

How embeddings turn words and documents into vectors, and how vector search powers semantic search, recommendations and modern AI apps.

What RAG is and why it matters: how connecting an LLM to a knowledge base produces accurate, up-to-date answers with fewer hallucinations.

How computers learn to "see" — from pixels and filters to convolutional networks that recognise objects, faces and scenes in images.

What the EU Green Deal means for youth and SMEs — climate goals, green funding opportunities and how organisations can get involved.

How large language models predict text, and the practical prompt-engineering techniques that get reliable, useful results from AI tools.