Roughgarden's class is advance and expects mathematical maturity. You may find his course quite fast and rough if you are a beginner.
Sedgwick's class is much easier. He is a bit boring and tries to use "real life" examples (in some instances) from the physical sciences to make the material relatable. This in my opinion detracts from the material. Also, he doesn't always fully explain where he got some of the big ohs here and there.
My advice? Follow MIT's OCW course (it uses CLRS). Supplement it with Algorithms Unlocked, the Khan Academy link in OP and CLRS. If you use those 4 resources and put in the work you'll understand the material.
All 4 sources have Thomas C's DNA touch to it (he is the C in CLRS). So you'll find it consistent when you read from one source to the other. After reading/hearing the same thing about 4 different times in 4 different ways it'll begin to click.
Order of easiness is probably Khan Academy > Algorithms Unlocked > MIT Algorithms Course > CLRS.
Algorithms Unlocked is like "pre-CLRS" and Khan Academy's version is the TL;DR version of Algorithms Unlocked.
Hope this helps.
Below are the links,
If you have to pick only one go with the MIT OCW, and snag a copy of CLRS. I got mine from my local lib. and it gave me more than enough time to work through the problem sets from the mooc.
I find there are a lot of online resources for those looking to learn algorithms and data structures but I've had trouble finding the same breadth and depth of resources surrounding the math behind CS (discrete math, probability, etc.). Any suggestions?
Where does Roughgarden's course fit in to this?