Master Generative AI Through a Complete Self-Study Path

From zero knowledge to practical, structured understanding in 10 carefully designed chapters.

This complete self-study guide is designed to help you understand how Generative AI systems actually work, how they are built, where they fail, and how they are applied in real-world scenarios.

No background in machine learning, mathematics, or programming is required. Every concept is explained from first principles, in plain English, with real-world analogies, diagrams, examples, failure modes, and scenario-based practice questions.

What this book covers:
- What Generative AI is, how LLMs work, and the core vocabulary: tokens, parameters, embeddings, context windows, temperature, and hallucination
- Prompt engineering: zero-shot, few-shot, chain-of-thought, function calling, and structured outputs
- Retrieval-Augmented Generation (RAG): chunking, vector search, semantic retrieval, grounding, and faithfulness evaluation
- Fine-tuning and adaptation: SFT, LoRA, QLoRA, RLHF, and when to use each approach
- Multimodal AI: vision-language models, diffusion models, CLIP, speech, documents, and video generation
- Enterprise Generative AI patterns: chains, agents, memory, guardrails, orchestration, cost, and latency
- Evaluation and benchmarking: BLEU, ROUGE, BERTScore, perplexity, LLM-as-judge, and benchmark contamination
- Ethics, safety, and responsible AI: bias types, alignment, jailbreaking, EU AI Act, GDPR, and the NIST AI Risk Management Framework

What makes this book different:
- Clarity over complexity: every concept is explained before technical depth is introduced
- Structure over randomness: each chapter builds logically on the previous one
- Application over memorization: scenario-based questions help you test real understanding
- Failure modes covered: not just what works, but what breaks, why it breaks, and how to mitigate it
- 150+ practice questions: chapter-end questions plus two full tests
- Weak-area diagnostic: identify exactly which chapters to revisit based on your mock exam results

Whether you are a professional transitioning into AI, a student building your foundation, an engineer working with AI-powered systems, or a learner preparing for Generative AI certifications, this book gives you a structured path from beginner-level understanding to confident, practical fluency.

Book 1 in the Applied AI Series.