Data Science: The Hard Parts by Daniel Vaughan (ISBN 978-1-098-14647-4)
← Previous: LLMs and the Future of Data Science
Seventeen chapters. Two parts. One preface that sets honest expectations. This series retold Daniel Vaughan’s Data Science: The Hard Parts chapter by chapter. Time to step back and say what stuck.
Data Engineering for Beginners by Chisom Nwokwu (ISBN 9781394325412, Wiley 2025)
Previous: Interview Questions Appendix
Thirteen chapters, an interview appendix, and a glossary later, here is where Data Engineering for Beginners lands.
The C++ Programmer’s Mindset by Sam Morley (ISBN 978-1-83588-842-1)
Fifteen chapters, one rubber duckies mystery, and a lot of code later, here is where The C++ Programmer’s Mindset lands.
Book: Data Engineering with AWS: A Comprehensive Guide to Building Robust Data Pipelines
Author: Brian Paul
ISBN: Not listed in the source edition
Book: Data Pipelines with Apache Airflow
Authors: Bas Harenslak, Julian deRuiter
ISBN: 9781617296901
Twenty-five posts later, I have read the whole book. Here is where I landed.
Book: Data Engineering with Python
Author: Paul Crickard
ISBN: 978-1-83921-418-9
Publisher: Packt (October 2020)
I finished the full walkthrough. Fifteen chapters, one appendix, two big projects, and a lot of terminal time. Here’s where I landed.
Book: Data Engineering with AWS: A Comprehensive Guide to Building Robust Data Pipelines
Author: Brian Paul
ISBN: Not listed in the source edition
Data Engineering for Beginners by Chisom Nwokwu (ISBN 9781394325412, Wiley 2025)
Previous: Building a Data Engineering Career
The appendix is a flashcard deck for interview prep. Nwokwu organized sample questions across five areas that match the interview stages from Chapter 13. I will retell the highlights here. Use this as a self-test before your next round.
Data Science: The Hard Parts by Daniel Vaughan (ISBN 978-1-098-14647-4)
← Previous: A/B Tests and Experimentation | Next: Series Closing
Chapter 17 is different. No techniques. No code snippets. Just speculation about what LLMs mean for data science.
The C++ Programmer’s Mindset by Sam Morley (ISBN 978-1-83588-842-1)
You picked C++ partly for speed. Chapter 15 is Morley’s case for measuring before you touch anything. Premature optimization wastes time and adds complexity. Profiling tells you where speed actually matters and what is holding you back.