Review : Stanford University Andrew Ng’s Machine Learning course at Coursera

I found this online course to be interesting, challenging, practical and it gave me some fresh ideas about problem solving using numerical methods.

What I liked most:

1) The lecture videos directly tied into the programming exercises.  You had a chance to directly try out what you just learned by programming it.

2) The automatic scoring/review of your programming assignments with the submit script was a great way to get instant feedback.

3) I was never bored listening to Andrew talk.  He worked very hard in making this material.

4) In the early sessions, there is quite a bit of linear algebra theory, and more importantly, some calculus of matrices.  This is advanced math, so I found it interesting to see how Andrew handled this.


What I wish was different:

1) The course uses Octave/Matlib which is no doubt a great tool, but not one that I am likely to use much given my long time experience with python.  He devotes some time early in the course to explain his selection, but I could still wish it used python with scikit-learn.

2) Some of quiz questions just didn’t make sense to me even though I tried my best.  At a certain point, I had to settle for a passing score rather then trying to repeat until perfect.

3) While I completed all the programming exercises and quizzes myself using only course provided materials, I am sure that everything needed to ace the course could be found via google.  This may take away from the final value of the certificate.



I have already been using my new skills in my interest in quant programming.  I would recommend this course to anyone who wants to get familiar with machine learning in a practical and hands-on manner.