Generative AI has become part of everyday life: writing, summarizing, translating, brainstorming, studying, organizing. Yet many people get disappointing results because they don't know how these tools work, or how to talk to them. This course gives you both: a clear picture of what happens under the hood, and a practical method for getting reliable, useful results.
Across six chapters you will see how AI, machine learning and language models relate, how to choose a tool, how to build a precise prompt and refine it, and how to use advanced patterns to control format, tone and structure. You will learn why models make mistakes, how to verify their output, how to spot bias, how to protect personal data, and what the main European rules (GDPR, EU AI Act) mean for an everyday user.
Throughout the course you build a running project: your own personal work assistant, a library of tested prompts for real tasks in your daily life (writing, summarizing, learning, organizing). In the final chapter you choose your tasks, document your prompts, evaluate them with a simple grid and write a personal charter for responsible use. Every lesson includes concrete examples and at least one hands-on exercise with a solution.
What you will learn
- Explain in plain words the difference between AI, machine learning and language models, and what "generative" really means.
- Describe how a model produces text (tokens, probabilities, training) and why it can get things wrong.
- Compare generative AI tools (chat, image, audio, code, multimodal; open or proprietary; free or paid) and choose one with clear criteria.
- Write structured prompts (role, context, task, format, constraints) and improve them with examples, step-by-step reasoning and iteration.
- Manage context and memory: long conversations, documents, custom instructions and knowing when to start fresh.
- Control the output (format, tone, length, templates) and apply patterns such as critique-then-improve, task decomposition and prompt chaining.
- Verify AI output, recognize hallucinations and bias, and protect personal and confidential data in line with GDPR principles.
- Build, test, document and evaluate your own prompt library, and write a personal charter for responsible use.
Prerequisites
No technical background needed. You should be comfortable using a web browser and typing text. Access to at least one generative AI assistant (a free version is enough) is recommended so you can try the exercises, but you can also follow the course by reading the examples.
Syllabus
Chapter 1 Understanding Generative AI
Chapter 2 The Fundamentals of Prompting
Chapter 3 Advanced Prompting
- Controlling the Output: Format, Templates, Tone and Length15 min
- Prompt Patterns: Personas, Critique, Decomposition and Chaining16 min
- Transform and Analyze: Summarize, Extract, Classify, Rewrite, Translate, Compare16 min
- Testing and Improving Your Prompts: Building Your Library16 min
- Quiz: Advanced Prompting5 questions