Intermediate friendly Free

Generative AI Engineering Tutorial

Build reliable generative AI systems with prompting, embeddings, RAG, tool use, agents, evaluation, safety, privacy, observability, and production controls.

  • 24lessons
  • 8modules
  • ~8hstudy time
  • Intermediatestart level
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What you will learn

  • Generative AI Foundations
  • Prompt Design
  • Embeddings and Retrieval
  • Retrieval-Augmented Generation
  • AI Application Patterns
  • Tools and Agents
  • Evaluation and Safety
  • Production AI Engineering

Course curriculum

8 modules · 24 lessons · follow them in order or jump to any topic

1 Generative AI Foundations 3 lessons
  1. 1Generative AI and Large Language Models
  2. 2Tokens, Context Windows, and Sampling
  3. 3Choosing a Model for a Task
2 Prompt Design 3 lessons
  1. 4Instructions, Context, and Constraints
  2. 5Few-Shot Examples and Structured Output
  3. 6Prompt Injection and Instruction Boundaries
3 Embeddings and Retrieval 3 lessons
  1. 7Embeddings and Semantic Similarity
  2. 8Chunking and Document Preparation
  3. 9Vector Search and Hybrid Retrieval
4 Retrieval-Augmented Generation 3 lessons
  1. 10RAG Architecture
  2. 11Reranking and Context Assembly
  3. 12Grounded Answers and Citations
5 AI Application Patterns 3 lessons
  1. 13Designing an AI Service
  2. 14Streaming Responses
  3. 15Conversation Memory
6 Tools and Agents 3 lessons
  1. 16Tool Calling
  2. 17Agent Loops and State Machines
  3. 18Sandboxing and Human Approval
7 Evaluation and Safety 3 lessons
  1. 19Building an Evaluation Dataset
  2. 20Scoring Quality and Groundedness
  3. 21Guardrails and Red Teaming
8 Production AI Engineering 3 lessons
  1. 22Cost, Latency, Caching, and Fallbacks
  2. 23Observability, Privacy, and Versioning
  3. 24Capstone: Build a Cited Knowledge Assistant

About this course

This tutorial suits complete beginners as well as learners who already know some programming and want a structured reference. If Generative AI Engineering is new to you, start from the first lesson and work through each module in order. Experienced learners can use the curriculum above to jump directly to a specific concept.

How to get the most from it

  1. Read each lesson in order and run every example yourself.
  2. Change the examples to test your understanding instead of only copying them.
  3. Complete the exercises and review the common-mistake sections before moving on.
  4. Mark lessons complete as you go — your progress is saved in this browser.

Frequently asked questions

Is this Generative AI Engineering tutorial free?

Yes. Every lesson listed on this page is free to read and can be completed at your own pace.

Do I need previous experience?

No previous experience is required for the introductory lessons. Some advanced modules are easier if you first complete the fundamentals in this course.

How should I practise?

Type and run the examples, deliberately change their inputs, predict the result before execution and build a small project after completing each major module.