Ebooks
Every programme as a workbook you can download and keep. Free, with nothing to sign up for.
Data Analyst & Business Intelligence
Twelve weeks, no programming assumed. R and Shiny as the core BI tool.
About the programmeApplied Data Analytics & Business Intelligence
Next Edition, by Pawan Rama Mali
The current edition of the twelve-week workbook. One chapter per week, from data foundations through SQL and statistics to R, Shiny and a deployed dashboard. Adds workflow diagrams and a modern-stack appendix over the first edition.
- 12 weekly chapters
- Workflow diagrams
- Modern-stack appendix
- Glossary
Free. No signup, no payment.
Exercises & Solutions
Companion workbook
Practice problems for every week of the programme, with worked solutions at the back. Meant to be attempted before you look, which is the only way it does anything for you.
- Problems per week
- Worked solutions
- Print-friendly
Free. No signup, no payment.
Applied Data Analytics & Business Intelligence
First edition
The original twelve-week workbook, kept available because links to it should not rot. The Next Edition above supersedes it.
- 12 weekly chapters
- Concept and pitfall boxes
- End-of-week projects
Free. No signup, no payment.
Artificial Intelligence
A 14-Week Introduction
Rules, search and learning taken apart on the same problem, then language, vision, fairness, explainability and governance. The comparisons were run rather than asserted, and several of them favour the unglamorous option.
- 14 chapters
- 98 lessons
- 112 questions with answers
- 140 code examples with output
Free. No signup, no payment.
Machine Learning
A 16-Week Practitioner Workbook
From a working model in week one through evaluation, feature engineering, unsupervised methods and neural networks to a model served over HTTP and watched for drift. Every method measured against a simpler baseline first.
- 16 chapters
- 112 lessons
- 128 questions with answers
- 416 code examples with output
Free. No signup, no payment.
Deep Learning
An 18-Week Advanced Workbook
Tensors and autograd up through convolutional networks, attention built by hand, transformers, GANs and diffusion, and the efficiency chapter that reports quantisation making inference slower and distillation losing.
- 18 chapters
- 126 lessons
- 144 questions with answers
- 292 code examples with output
Free. No signup, no payment.
What is actually in them
The three course workbooks are the published lessons in book form, so nothing is held back for the paid version, because there is no paid version. Every code example appears as it was run and its printed output sits underneath it, including the runs that undercut the technique being taught. Each chapter ends with the self-assessment questions and their answers.
They are revised when the courses are. Leave an email and we will tell you when a new edition lands, and nothing else.
Using these with a team?
The books and the curriculum are free to hand to anyone, including a whole department. If you want the material shaped around your own data and tools, or a group taken through it rather than left to it, that is a conversation rather than a signup form.