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Preface

Published

2026-11-06

NoteUpdate

All of the exercises in this book were completed using Pop!_OS the COSMIC Desktop Environment from System76.

This book contains my solutions to the labs in do4ds, applied to my work as a Posit System Administrator. The original labs are available in the GitHub repo:

https://github.com/akgold/do4ds

Why publish a lab solution manual?

Working through the lab solutions in each chapter gave me a better understanding of ‘DevOps conventions, tools, and practices’ and helped me work better with the IT/Admin team at my organization.1

More importantly, this online version of solutions provides examples of what each chapter looks like in my organization. Working through the labs (i.e., getting the code to run in R and Python) and creating diagrams/summaries made the topics more concrete and applicable.

Why not just use LLMs to find the answers?

LLMs aren’t covered in do4ds, but the release of ChatGPT at the end of 2022 marked the beginning of a major change in how data science code and projects are developed. The initial LLMs weren’t great at writing code, but they have improved significantly.2 By the end of 2025 (the approximate date I started publishing my lab solutions), the R/Python ecosystem had produced a variety of packages and tools for using LLMs.3

I’ve found using Claude is very helpful in expanding on topics, building mermaid diagrams, and generating ideas for troubleshooting bugs/errors. Using LLMs to supplement learning any topic makes the information stick more than just asking for an answer. For example, I’d use the code in each lab as a starting point and develop a solution until I ran into a bug or issue. Then, I’d check my understanding with the LLM and confirm Claude’s responses with source documentation. This iterative process made me recall and use the topics in my daily work as a Posit System Administrator.

I don’t ask for direct solutions to problems or to provide answers to comprehension questions because I’ve found this doesn’t stretch my ability to formulate my own answers (or recall the information later).4

  1. This is a direct quote from the book’s intro.↩︎

  2. Anthropic’s Claude model (released in March 2023) was the first LLM I used that had a notable increased ability to answer R and Python coding questions.↩︎

  3. Check out the Posit AI blog or Luis D. Verde Arregoitia’s book, Large Language Model tools for R.↩︎

  4. This is consistent with recent research on using LLMs in educational settings.↩︎