People at Berkeley view this class as kind of a joke. The average grade is insanely high and the topics are covered in much less depth than just the normal intro cs or stats classes.
But I think I'd like some kind of formal, credentialed program that would build on my existing linear algebra + software skills (and address the weaknesses in my statistical understanding that I know are there based on how I felt about my grasp on the related material for even the classes I passed)... and maybe isn't quite as big an investment as a full-fledged master's degree.
Anybody have any suggestions?
It is a big commitment - 6 months full-time or one year part-time.
Depending on what stats you want to do, there are some pretty decent MOOCs. No one is going to claim that Daphne Koller's PGM course is weak in anyway for example[1].
[1] https://www.coursera.org/learn/probabilistic-graphical-model...
Which are the hard courses at Berkeley in CompSci using the site you linked?
If my memory holds, there’s a policy that class averages should be around 3.0-3.3 (B/B+).