AI ENGINEER: FROM FOUNDATIONS TO PRODUCTION (English Edition) pdf

Build the skills and judgement to take AI from foundations to production.

Creating dependable AI systems requires decisions about data, architecture, evaluation, security, cost, and the people who will operate them.

AI Engineer — From Foundations to Production brings those decisions to life through the journey of Peter Halloway, an engineer at a fictional investment bank in London. What begins as a challenge to create reliable test data grows into a programme spanning machine learning, synthetic data, large language models, and intelligent agents.

Across 56 chapters, Python examples, practical exercises, and a continuous case study help you connect technical concepts to business problems.

Inside, you will learn how to:

• Choose the right approach by matching business needs to deterministic code, machine learning, language models, or agents.
• Evaluate models with confidence using meaningful baselines, repeatable experiments, and measures that reflect the intended use.
• Create useful synthetic test data while addressing consistency, reproducibility, and privacy risks.
• Connect language models to enterprise knowledge through retrieval-augmented generation, access controls, and traceable answers.
• Design agents with clear boundaries, human approval, controlled tool use, and recovery strategies.
• Plan for production realities, including latency, operating costs, monitoring, security, and model governance.
• Communicate architectural decisions and build processes that other people can maintain and improve.

Written for software developers, QA professionals, data engineers, architects, and technical leads, this book offers a practical path into the responsibilities of an AI engineer. Familiarity with basic programming will help you get the most from the examples.

Follow the project through experiments, setbacks, incidents, and reviews—and see how each decision shapes the system that emerges.

Learn to explain your choices, test your assumptions, and build AI systems your organisation can operate and improve.