Machine Learning Coursera Course Review

Machine Learning is one of the first programming MOOCs Coursera put online by Coursera founder and Stanford Professor Andrew Ng. Although Machine learning has run several times since its first offering and it doesn’t seem to have been changed or updated much since then, it holds up quite well. This course assumes that you have basic programming skills. Assignments also require many vector and matrix operations and slides include some long formulas expressed in summation notation so it is recommended to have some familiarity with linear algebra. You don't need to know calculus or statistics to take this course, but you may gain deeper insight into some of the material if you do. The course uses the Octave programming language, a free clone of MATLAB.

The course runs 10 weeks and covers a variety of topics and algorithms in machine learning including gradient descent, linear and logistic regression, neural networks, support vector machines, clustering, anomaly detection, recommender systems and general advice for applying machine learning techniques. Lectures are split into 3 to 15 minute segments with periodic quizzes and each topic section has a corresponding quiz. Section quizzes are worth 1/3 of the total grade but you get unlimited attempts (with a 10-minute retry timer.). Andrew Ng does a good job explaining dense material and slides although the audio levels are often too low. If you don' have good speakers you might need headphones to hear him talk. The other 2/3 of the course grade is based on 8 multi-part programming assignments that typically involve filling in code for key functions to implement machine learning algorithms covered in lecture. The course gives you a lot of structure and direction for each homework, so it is generally pretty clear what you are supposed to do and how you are supposed to do it even if you don't understand 100% of the materiel covered in lecture. You need to achieve a total score of 80% to earn a certificate, so while you can retry quizzes and resubmit programming assignments you'll have to get most things to work in the end to get one.

Machine learning is a great course if you can get past quiet audio. If you've never used Octave or MATLAB before, don't let that stop you from taking this course: learning the basics necessary to do the assignments only takes a couple of hours and it will help you think of things in terms of vectorized operations.

I give this course 4.5 out of 5 stars: Great.