leehanchung / awesome-full-stack-machine-learning-courses
Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.
Why this job: name: awesome; says: curated list
What it does
This is a curated list of publicly accessible machine learning courses from top universities such as Berkeley, Harvard, Stanford, and MIT. It also includes machine learning project case studies from large and experienced companies. The list is broken down by topics and areas of specialization. Python is the preferred language of choice as it covers end-to-end machine learning engineering.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 7 months ago
- Stars
- 538
- On GitHub
- Licence
- CC0-1.0
- Read the terms
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- JavaScript
- 57% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 0% closed
- 1 still open
- Pull requests
- 1 merged
- 8 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- JavaScript 57%
- CSS 22%
- Python 21%
Topics
- machine-learning
- deep-learning
- deep-neural-networks
- berkeley
- reinforcement-learning
- stanford
- udemy
- caltech
- columbia-university
- berkeley-ai
- berkeley-reinforcement-learning
- edx-columbiax
Project record
- JobLists and guides
- StatusListed
- Commits91
- Forks111
- Watching7
- Stars in 28 days+2
- CreatedOct 31, 2019
- First seen by usNov 7, 2026
- CheckedNov 8, 2026



