Here's a list of advanced courses about ML:

1. [Advanced Introduction to ML](http://www.cs.cmu.edu/~bapoczos/Classes/ML10715_2015Fall/index.html)  - [videos](https://www.youtube.com/playlist?list=PL4DwY1suLMkcu-wytRDbvBNmx57CdQ2pJ&amp;jct=q4qVgISGxJql7TlE6eSLKa8Wwci8SA)

2. [Large Scale ML](http://www.cs.toronto.edu/~rsalakhu/STA4273_2015/) - [videos](http://www.cs.toronto.edu/~rsalakhu/STA4273_2015/lectures.html)

3. [Statistical Learning Theory and Applications](http://www.mit.edu/~9.520/fall15/index.html) - [videos](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O)

4. [Regularization Methods for ML](http://lcsl.mit.edu/courses/regml/regml2016/) - [videos](https://www.youtube.com/playlist?list=PLbF0BXX_6CPJ20Gf_KbLFnPWjFTvvRwCO)

5. [Statistical ML](http://www.stat.cmu.edu/~larry/=sml/) - [videos](https://www.youtube.com/playlist?list=PLTB9VQq8WiaCBK2XrtYn5t9uuPdsNm7YE)

6. [Convex Optimization](http://www.stat.cmu.edu/~ryantibs/convexopt-S15/) - [videos](https://www.youtube.com/playlist?list=PLjbUi5mgii6BZBhJ9nW7eydgycyCOYeZ6)

7. [Probabilistic Graphical Models 2014 (with videos)](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html) - [PGM 2016 (without videos)](http://www.cs.cmu.edu/~epxing/Class/10708-16/lecture.html)

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Please let me know if you know of any other *advanced* (Phd-level) courses. I don't mind if there are no videos, but I don't like courses with no videos ***and*** extra concise and incomprehensible slides.

And no, CS229 is *not* advanced!

Phd-level courses