Books

Mathematical Foundations of AI and Data Science: Discrete Structures, Graphs, Logic, and Combinatorics in Practice transforms abstract mathematical concepts into practical tools for computational problem-solving.Explore logic, set theory, relations, functions, combinatorics, discrete probability, graph algorithms, trees, algebraic structures, Boolean systems, recurrence relations, optimization.

Built around the CISO's Decision Journey — a five-stage loop of Assess, Govern, Defend, Monitor, and Improve — this book across fourteen chapters moves from the AI threat landscape and the regulatory environment to threat modelling and red teaming, a layered security-controls architecture, AI incident response, the AI-assisted SOC, and a 90-day programme roadmap.

Build a powerful AI assistant that runs entirely on your own hardware. The Ollama Assistant Handbook takes you from installation to a production-ready assistant with memory, tools, voice, vision, and automation through practical, hands-on examples you can use immediately.

AI can generate code in seconds, but shipping production-grade software requires far more than fast prompts. Vibe Engineering shows you how to work with AI coding assistants to build systems that are reliable, secure, and maintainable. Through practical examples and proven workflows, you will learn how to turn AI from a code generator into a trusted engineering partner.

Most businesses use only a fraction of what Claude can actually do. The difference between average results and real business impact is not the AI. It is the prompt. This book gives you 100 proven Claude prompts for solving high-value business problems, complete with practical guidance so you can implement them immediately and turn AI into a competitive advantage.

Advanced Prompt Engineering for LLMs: 2026 Techniques That Actually Deliver Results takes readers beyond basic instructions and introduces a complete system for working with modern Large Language Models.Discover how to:• Apply powerful frameworks such as RACE and TREE • Build advanced multi-layer prompts • Use meta-prompting to create and improve prompts • Design specialized expert personas

Go beyond simple chatbots and build production-ready AI agents with LlamaIndex. Through practical projects and working Python code, you will learn to design reliable systems with retrieval, workflows, multi-agent architectures, observability, and deployment techniques for real-world applications.

Run powerful AI models directly in the browser with no servers and no cloud dependencies. LiteRT.js teaches you how to build fast, private, and production-ready machine learning applications using WebAssembly, WebGPU, and WebNN, with practical examples and performance-focused techniques throughout.

Discover how to build production-ready AI agents and multi-agent systems with CrewAI. Through practical examples and real-world projects, you will learn to create autonomous agents that collaborate, use tools, integrate with external data, and scale from prototype to production.

Learn how to build intelligent, production-ready AI agents with the OpenAI Agents SDK. Through practical Python examples and step by step guidance, you'll master everything from the fundamentals to advanced multi-agent workflows, tools, and deployment.

Build intelligent AI applications with LangChain using practical, production-ready Python examples. From intelligent agents and retrieval-augmented generation to scalable deployment and observability, this book equips you with the skills and architectural understanding needed to create reliable, real-world LLM-powered systems.

An LLM is not an AI system.Systems Thinking for Agentic AI shows software engineers and architects how to design reliable AI applications with prompts, RAG, tools, memory, orchestration, guardrails, evaluation, observability, and runtime control.Move beyond chatbot demos and learn how to build production-ready agentic AI systems you can reason about, measure, debug, operate, and improve

Learn how to build autonomous, production-ready multi-agent AI systems in C# with .NET. Using Harness, Hermes Agents, and Loop Engineering, you'll create intelligent agents that reason, collaborate, and solve real-world problems through practical examples and hands-on projects.