Generative AI The Complete Self-Study Guide (Applied AI Series Book 1)

Generative AI: The Complete Self-Study Guide (Applied AI Series Book 1)
English | May 18, 2026 | ASIN: B0GX38WMJM | 242 pages | PDF | 53.39 MB
Master Generative AI Through a Complete Self-Study PathFrom 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 hallucinationPrompt engineering: zero-shot, few-shot, chain-of-thought, function calling, and structured outputsRetrieval-Augmented Generation (RAG): chunking, vector search, semantic retrieval, grounding, and faithfulness evaluationFine-tuning and adaptation: SFT, LoRA, QLoRA, RLHF, and when to use each approachMultimodal AI: vision-language models, diffusion models, CLIP, speech, documents, and video generationEnterprise Generative AI patterns: chains, agents, memory, guardrails, orchestration, cost, and latencyEvaluation and benchmarking: BLEU, ROUGE, BERTScore, perplexity, LLM-as-judge, and benchmark contaminationEthics, safety, and responsible AI: bias types, alignment, jailbreaking, EU AI Act, GDPR, and the NIST AI Risk Management FrameworkWhat makes this book different:Clarity over complexity: every concept is explained before technical depth is introducedStructure over randomness: each chapter builds logically on the previous oneApplication over memorization: scenario-based questions help you test real understandingFailure modes covered: not just what works, but what breaks, why it breaks, and how to mitigate it150+ practice questions: chapter-end questions plus two full testsWeak-area diagnostic: identify exactly which chapters to revisit based on your mock exam resultsWhether 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.