The book gives a beginner-friendly walkthrough of AI and machine learning: it starts by explaining how artificial intelligence, machine learning, deep learning, and generative AI relate to one another, then covers the machine learning workflow (data, algorithms, training, inferencing), neural networks and deep learning applications like computer vision and NLP, and generative AI fundamentals (foundation models, LLMs, tokens/embeddings, diffusion models, multimodal models, GANs, and VAEs). It closes with how these models are optimized in practice through prompt engineering, fine-tuning, and retrieval-augmented generation (RAG), plus a glossary of key terms for quick reference.