✨ Prompt Engineering & Generative AI at Work

A free, practical, trilingual course on using large language models (LLMs) such as ChatGPT, Claude, Gemini and Microsoft Copilot productively and safely at work. Learn how generative AI really works, master proven prompt-engineering patterns (zero-shot, few-shot, chain-of-thought, role and structured prompts), ground answers with retrieval-augmented generation (RAG), evaluate and iterate on outputs, and apply responsible-AI guardrails for privacy, bias, hallucination and security. Includes rich visual lessons, original practice questions and a 10-question final exam (80% to pass). The course is organized into 7 modules, ending with a final exam (pass mark 80%). It is free awareness-level training designed for anyone who needs a practical, working understanding of the topic.

What you'll learn

• Module 1 — How Generative AI & LLMs Work
• Module 2 — Anatomy of a Good Prompt
• Module 3 — Core Prompting Patterns
• Module 4 — Parameters, System Prompts & Context
• Module 5 — Grounding with RAG & Custom Data
• Module 6 — Evaluating & Iterating on Outputs
• Module 7 — Responsible & Secure Use at Work

Learning objectives

• Explain in plain terms how large language models generate text: tokens, embeddings, context windows and next-token prediction
• Recognise the strengths and limits of generative AI, including hallucination, bias, knowledge cut-off and non-determinism
• Write clear, structured prompts using role, task, context, format and constraints
• Apply core prompting patterns: zero-shot, few-shot, chain-of-thought, role prompting and decomposition
• Tune model behaviour with inference parameters (temperature, top-p, max tokens) and a system prompt
• Ground answers in your own data with retrieval-augmented generation (RAG) instead of fine-tuning where possible
• Evaluate, test and iteratively improve prompts and outputs with human review and simple metrics
• Apply responsible-AI guardrails for privacy, security (prompt injection), fairness and human oversight
• Sit a 10-question final exam (80% to pass) built from original, scenario-based questions