I took his 2 algorithm courses on Coursera's original platform. They were stellar. In particular making practical problems that have a calculable answer that you implement yourself in whatever language you choose and check as part of the course. As opposed to having some online interpreter for some specific language.

That was then hosted on Stanford's own Lagunita platform (based on the edX platform I think.)

Stanford then split those 2 courses into 4 on Coursera's new platform - the same material I believe but packaged differently.

Stanford then closed its Lagunita platform and those original 2 courses are now offered on edX.

A similar story with Alex Aiken's excellent Compiler course and Jeffrey Ullman's Automata course too. I'm not even sure if they are still available on Coursera or not.

[1] https://www.edx.org/course/algorithms-design-and-analysis

[2] https://www.edx.org/course/algorithms-design-and-analysis-pa...

[3] https://www.edx.org/course/compilers

[4] https://www.edx.org/course/automata-theory

What level of math would you recommend for the courses?

This is always a difficult question, because it's always "high school level math" which is rarely true. Then again, some algo courses focus highly on math and proofs while others focus more on implementation.

I prefer the Algorithms course by Princeton but I still really like this course. The deep dive into the mathematical proofs and timing of these algorithms is what gives this course an advantage over Princeton’s course.

Highly recommend this course. Good coverage of topics and the explanations help build intuition.