Data Science with Generative AI - Volume 2: Data Analytics

Volume 2 — Data Analytics

Chapters 11–32. The volume where an analyst's SQL and spreadsheet instincts turn into real data-science skills. You'll rebuild the math and statistics you actually need (with intuition first, Python second), learn to interrogate real databases with SQL, collect data from APIs responsibly, build data engineering pipelines that scale with tools like Spark, and — critically — learn to ask sharp analytical questions and draw honest charts before you ever model anything. It closes with dashboards and using AI as an analysis partner you still have to check.

Who it's for: analysts and BI/spreadsheet people moving into data science, and anyone who wants the data-handling foundation the rest of the series builds on.

What you get: PDF + EPUB of Volume 2. (Book + Resources adds runnable code files/notebooks for every chapter.)

At 432 pages, this is the longest single volume outside the production volume — deliberately, since it's the part most people underinvest in before jumping to modelling.