Machine Learning and AI Stanford Course


I would like to draw your attention to a unique Stanford University initiative. In this season, the first time ever, you can participate in a unique research project that intends to change the future of the education.

Stanford University has announced to make 2 courses available online Worldwide!

-Introduction to Artificial Intelligence

-Machine Learning

An exceptional thing about this course (compared to other online courses like the MIT online courseware) that it is not simply viewing offline videos later, anytime when you have free time, but you do homework, assignments, test, and exams as you would do it in a case if you are really a Stanford University student. You even get a certificate about the completion and certificate of your own results, comparing your results to the rest of the ‘world’. 🙂

The writer of this blog is very pleased with this announcement because of:

– the firm belief that the ‘teacher’ as a job will be mostly outdated in the next century. I reckon in 30 years we will need only 10% of the teachers as we have now.

– I welcome the integration of universities/courses. This is the most efficient way to distribute the best tutors to the widest audience. I would like to see only the best 500 universities in the world to survive than having 5000 (poor) universities scattered all around. Having 5000 universities is very inefficient/costly way of distributing knowledge.

– I welcome the idea that the knowledge is public. Available to anyone from the skyscrapers of New York to the slums of India. No means testing, no university fees. Everyone is equal and it is possible for everyone (with enough diligence) to achieve university degree.

Topics include:

supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.


Probability and linear algebra is a requirement, of course.

There are 140K students applied for the Artificial Intelligence course and about 60K for the more advanced Machine Learning course.

Note that there are 2 kinds of virtual students: One that follows only the videos (spectators), but do no homework or tests. They receive no certification.

Currently, it is not published what percentage of the students are in the spectators club. And the truth is that you can change your status later during the term. If you find that you don’t have enough time, you can switch to be a spectator anytime.

The homepages:

Note the time requirement tough:

Stanford advices to spend 10 hours per week on one course. That means 20 hours per week for the two courses. Those who don’t have enough spare time can consider taking only the simpler Artificial Intelligence course only, albeit take into account if the Machine Learning course don’t start next year (then you missed your chance).

We encourage everybody who has some time to take part in these excellent initiatives and become a student of Stanford University and be (a little) proud that you participate Now in something that is the future of university level education.


One Response to “Machine Learning and AI Stanford Course”

  1. 1 jdfagan

    Did you take Andrew Ng’s class?

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