The Curriculum¶

Thirteen volumes, ordered so that each one only assumes what came before it. You can skip forward, but the prerequisites are real — Volume 6 will not make sense without Volume 5, and Volume 5 will not make sense without Volume 2.

flowchart TD
  V1[1 · CS Foundations] --> V2[2 · Python]
  V2 --> V3[3 · Software Engineering]
  V2 --> V4[4 · Data Engineering]
  V4 --> V5[5 · Data Science]
  V5 --> V6[6 · Machine Learning]
  V6 --> V7[7 · Deep Learning]
  V7 --> V8[8 · LLMs]
  V8 --> V9[9 · RAG]
  V9 --> V10[10 · AI Agents]
  V6 --> V11[11 · MLOps]
  V3 --> V12[12 · Enterprise Engineering]
  V11 --> V13[13 · Capstones]
  V12 --> V13
  V10 --> V13

The volumes¶

#	Volume	Focus	Status
1	Computer Science Foundations	How machines actually work	Partly available
2	Python Programming	The language, properly	Available now
3	Professional Software Engineering	Turning scripts into systems	Available now
4	Data Engineering	Moving data reliably	Partly available
5	Data Science	From data to defensible conclusions	Partly available
6	Machine Learning	Models that generalise	Outlined, not yet written
7	Deep Learning	Neural networks, understood	Outlined, not yet written
8	Large Language Models	What they are and what they are not	Outlined, not yet written
9	Retrieval-Augmented Generation	Grounding models in your data	Outlined, not yet written
10	AI Agents	Systems that take actions	Outlined, not yet written
11	MLOps	Models in production	Outlined, not yet written
12	Enterprise Engineering	Designing systems at scale	Available now
13	Enterprise Capstones	Proof you can do the job	Available now

On status labels

This course is being written in the open. Available now means the lessons exist and are complete. Outlined means the chapter plan is fixed but the prose is not yet written. Labelling that honestly is more useful to you than a table of links that lead nowhere.

The Version 1 course¶

Every lesson from the original edition has been migrated and is available in full:

Browse the migrated course