Project Management in AI

This book is your ultimate guide to Project Management in AI. It takes you deep into the CPMAI methodology. Traditional software development lifecycles do not work here. Artificial intelligence is completely different. It deals in likelihoods, not certainties. This book explains the six critical phases of an AI project. You will learn how to align business goals with technical feasibility. We explore how to source, clean, and prepare datasets. You will discover how to select algorithms and train models. We tackle model evaluation and strict business validation. Finally, the book guides you through operationalization and MLOps. It covers the seven specific patterns of AI. You will navigate ethics and global data governance laws. It teaches you to manage risks like model drift and epistemic debt. You will explore synthetic data generation and federated learning. Every chapter breaks down complex concepts into manageable tasks.

What sets this book apart from the rest of the tech management guides out there? Most AI books focus entirely on writing Python code or math, ignoring the business reality that gets projects funded. Conversely, traditional project management books try to force rigid Waterfall or Agile frameworks onto AI, leading to wasted budgets. This book bridges that exact gap. It transforms you into a "T-Shaped Translator" who speaks the language of the boardroom and the data lab. It provides a unique framework for managing the probabilistic nature of machine learning. You get real-world strategies for calculating hard and soft ROI, and surviving regulatory audits like the EU AI Act. It is not just about building a model; it is about scaling an AI portfolio profitably in the modern enterprise.

Think of me as your mentor through the AI trenches. We dive into why data needs a "nutrition label" and how to construct Model Cards to build trust. You will see how to balance compute budgets and handle Shadow AI. We also help you overcome "Algorithm Aversion" by shifting the narrative from AI replacing workers to augmenting them. Authored by Azhar ul Haque Sario, an experienced data scientist, this guide is packed with actionable insights for the 2026 tech landscape.

Copyright Disclaimer: This book is independently produced for educational purposes by Azhar Sario Hungary. The author has no affiliation with any official board, and all frameworks mentioned are used purely under nominative fair use.