CMU Online

Education and knowledge should be accessible to anyone who is willing to learn. There are many great course offerings from the top-ranked Computer Science program in Carnegie Mellon University whose lectures are available on the public domain. The purpose of this page is to curate these courses, so people can self-study and learn from the best professors in the world without the hefty college price tag. I hope that this resource will be helpful for both people currently in industry aiming to improve their knowledge, current students to make course decisions or to do self-learning, and even prospective students to get a taste of what a CMU education looks like. In addition to courses, I have also included links to weekly seminar series which are held by various research groups for people interested in getting closer to state-of-the-art developments.

Courses which are accessible to undergraduates will have a tag. This does not mean that the difficulty is not suitable for graduate students; on the contrary, almost all such classes are cross-listed as graduate courses and are commonly taken by graduate students at CMU. There are also some graduate classes (based on the course number) which are suitable for advanced undergraduates which I marked as undergraduate as well. Classes that require significant background and which are less accessible will have a tag.

Some courses are only publicly available on Panopto instead of Youtube, in which case I provided a link to the Panopto playlist. Don’t feel too sad that this is the case, because it can be more conducive to use Panopto than Youtube due to the ability to customize speaker and presentation view.

Within each category, the courses are not ordered in any particular way that is indicative of difficulty or the order in which they should be taken. Consider it to be arbitrary.

Please let me know if there are any dead links, or if you spot an error with the page. In addition, if there are courses that I missed which might be useful for others, you can either modify the relevant data file here and make a pull request, or let me know via email. I will very much appreciate it!

The list of courses available publicly is heavily skewed towards which departments or faculty members make their lecture recordings publicly available, and therefore omits a lot of classes that Computer Science majors in CMU tend to take. In particular, courses from the following departments in the School of Computer Science are not present: Computational Biology, Human-Computer Interaction, Institute for Software Research.

The contents on this page is personally curated and does not reflects the views of CMU or SCS, and is also not endorsed by either parties.

Machine Learning

The machine learning courses in this section generally assumes working knowledge of probability, statistics, calculus, and linear algebra. 10-701 Introduction to Machine Learning or 10-715 Advanced Introduction to Machine Learning are the recommended pre-requisites for most of these courses if you do not have taken any prior machine learning classes. Both of these introductory courses are also available in the table below.

Computer Systems

15-213 Introduction to Computer Systems is a required course for all CS majors in CMU, and is the pre-requisite for all subsequent systems classes. It is a good place to start if you are new to computer systems. In most other universities, this class is usually referred to as an operating systems class.

Computer Science Theory

15-251 Great Ideas in Theoretical Computer Science is the introductory CS theory class taken by CS majors in their first year, and would be a good place to start if you are new to CS theory. All subsequent theory classes assumes knowledge from 15-251.

Programming Language Theory

Unfortunately, there are not a lot of publicly available programming language (PL) theory lectures. However, Robert Harper and Jan Hoffmann, staples of the PL scene in CMU, both frequently give lectures for the Oregon Programming Languages Summer School that are much smaller in scope than what is covered in a comparable full-semester course in CMU, but still goes through many key ideas nonetheless. Therefore, I have also decided to include these resources than not have anything, which would be a shame as CMU is a powerhouse in PL after all.

Why are so many courses titled 15-819? This is because the course number is a catch-all for advanced topics in PL theory, so while the course name is the same, the content can vary.

15-312 Foundations of Programming Languages is the introductory class of the PL track, and would be a good place to start. The other introductory PL class 15-317 Constructive Logic unfortunately does not have any publicly available lectures.

Computer Graphics

Robotics

Mathematics and Statistics

In general, the math department does not record any of their lectures, so this portion is pretty dry. However, it was worth having it just to include Po-Shen Loh’s lectures. He coaches the USA IMO team and is well-loved by his students.