Free Self-Paced Course

Intermediate Data Science

9 Weeks · 278 Pages · Computer Science — Data Science

This free, self-paced course provides a structured 9-week syllabus for learning Intermediate Data Science. Each module builds on the previous one, guiding you from foundational concepts through advanced topics with 278 pages of in-depth reading material. All content is drawn from our comprehensive Intermediate Data Science textbook, organized into a clear weekly schedule that you can follow at your own pace.

Modules

278

Pages

Self-Paced

Free

Always Free

Weekly Syllabus

1 Frontmatter

2 Part I: The ML Mindset

3 Part II: Feature Engineering and Data Preparation

4 Part III: Supervised Learning

5 Part IV: Unsupervised Learning

6 Part V: Specialized Data Types

7 Part VI: From Notebook to Production

8 Part VII: Synthesis

9 Appendices

How to Use This Syllabus

Read at your own pace. Each module is designed for roughly one week of study, but there are no deadlines. Spend as much time as you need on each topic.
Follow in order or jump around. The modules are arranged sequentially for a structured learning path, but feel free to skip to any topic that interests you most.
No sign-up needed. Every page in this syllabus links directly to free, open-access content. Just click a topic and start reading immediately.

Ready to Start Learning?

Access the full Intermediate Data Science textbook with all chapters, examples, and exercises.

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