This was in the pipeline for quite some time now. I have been waiting for his lectures on a platform such as EdX or Coursera, and the day has arrived. You can enroll and start with week 1’s lectures as they’re live now.

This course is taught by none other than Dr. Yaser S. Abu – Mostafa, whose textbook on machine learning, **Learning from Data** is #1 bestseller textbook (Amazon) in all categories of Computer Science. His online course has been offered earlier over here.

**Teaching**

Dr. Abu-Mostafa received the Clauser Prize for the most original doctoral thesis at Caltech. He received the ASCIT Teaching Awards in 1986, 1989 and 1991, the GSC Teaching Awards in 1995 and 2002, and the Richard P. Feynman prize for excellence in teaching in 1996.

**Live ‘One-take’ Recordings**

The lectures have been recorded from a live broadcast (including Q&A, which will let you gauge the level of CalTech students taking this course). In fact, it almost seems as though Abu Mostafa takes a direct jab at Andrew Ng’s popular Coursera MOOC by stating the obvious on his course page.

A real Caltech course, not a watered-down version

Again, while enrolling note that this is what Abu Mostafa had to say about the online course: “*A Caltech course does not cater to short attention spans, and it may not provide instant gratification…[like] many MOOCs out there that are quite simple and have a ‘video game’ feel to them.*” Unsurprisingly, many online students have dropped out in the past, but some of those students who “*complained early on but decided to stick with the course had very flattering words to say at the end*”.

**Prerequisites**

- Basic probability
- Basic matrices
- Basic calculus
- Some programming language/platform
*(I choose Python!)*

If you’re looking for a challenging machine learning course, this is probably one you must take.

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