Angelica Lo Duca

Angelica Lo Duca is a researcher at the Institute of Informatics and Telematics of the National Research Council, Italy. She is also an adjunct professor of Data Journalism at the University of Pisa. Her research interests include data storytelling, data science, data journalism, data engineering, and web applications. In the past, she worked with topics such as network security, semantic web, linked data, and blockchain. She has published over 40 scientific papers at national and international conferences and journals. She has participated in different national and international projects and events. She is the author of the book Comet for Data Science (Packt Publishing, 2022) and coauthor of the book Learning and Operating Presto (O’Reilly Media, 2023).

books by Angelica Lo Duca

Understanding AI

  • MEAP began August 2026
  • Last updated August 2026
  • Publication in Spring 2027 (estimated)
  • ISBN 9781633435193
  • 225 pages (estimated)
  • printed in black & white
resources: Book forum

Generative AI has quietly become part of everyday work. It writes emails, summarizes reports, drafts code, generates images, and answers questions in seconds. If you want to maximize the power of AI in your day-to-day, this is the book for you!

Understanding AI: A beginner’s guide is a practical, accessible introduction to generative AI for professionals, educators, managers, students, and content creators who want to understand how AI models, applications, and agents work so they can use it effectively. Based on author Matthew Berman’s wildly popular YouTube videos, this entertaining and insightful book guides you from square one without a lot of math, code, or technical jargon.

Authors Matthew Berman, Angelica Lo Duca, and Nick Wentz take you step by step through the patterns behind modern AI systems, providing a clear picture of how they do what they do, how to steer them toward the results you actually want, and where their limits truly lie. You’ll start with the fundamentals of how large language models generate text, then explore prompt engineering techniques that separate mediocre outputs from genuinely useful ones. You’ll learn how to compare commercial and open models, how to know when a small model is a smart choice, and how to match the right tool to the task in front of you. You also look at techniques like retrieval-augmented generation—or RAG—for grounding LLM responses in real information and understand how AI agents complete multi-step work on your behalf.

Just as importantly, Understanding AI: A beginner’s guide takes the limitations of generative AI seriously. Hallucinations, bias, privacy concerns, and the temptation to over-trust confident-sounding outputs are treated as core topics, not footnotes. You’ll finish each chapter with a short scenario that shows how AI plays out in real workplace situations, so the concepts stick and the tradeoffs feel real.

This book won’t lock you into one platform or one vendor. AI tools will keep changing, and the book gives you the durable skills to keep pace. Read it once as an introduction, then return to it as a reference whenever a new model, new capability, or new question shows up in your work.

Data Storytelling with Altair and AI

  • August 2024
  • ISBN 9781633437920
  • 384 pages
  • printed in black & white

Data Storytelling with Altair and AI teaches you how to build enhanced data visualizations using these tools. The book uses hands-on examples to build powerful narratives that can inform, inspire, and motivate. It covers the Altair data visualization library, along with AI techniques like generating text with ChatGPT, creating images with DALL-E, and Python coding with Copilot. You’ll learn by practicing with each interesting data story, from tourist arrivals in Portugal to population growth in the USA to fake news, salmon aquaculture, and more.