Most AI tutorials stop where the real work begins.
This book covers what happens after the demo works: LLMs, prompting, embeddings, vector search, RAG, agents, MCP, evaluation, guardrails, deployment, architecture, and cost.
7 parts. 28 chapters. 5 complete projects. 260+ diagrams.
You’ll learn how to build real-world AI systems, avoid common mistakes, make better engineering decisions, prepare for AI Engineer interviews, build a strong portfolio, and follow a practical 6-month roadmap.
Perfect for software engineers, students, career changers, ML/data professionals, and tech leads who want a clear path into AI Engineering.
Learn → Build → Evaluate → Deploy → Improve
Instant download with lifetime access and future updates.
Written by Manoj Kumar
AI Solution Engineer · manojofficial.com