First, even though STATS 100A is a prereq for this class, it isn't too stats heavy, so if you want to take this without having taken STATS 100A, talk to the TAs or the prof and they'll probably let you in.
This class is an interesting application of algorithms in biology, and largely was divided into the following:
1. Sequence Alignment to the Genome (Leetcode string problems, but on large strings)
2. Assembly (graph traversal problems/ path finding problems)
3. RNA Sequencing (more string problems, dynamic programming)
4. Hidden Markov Models

I found the material to be pretty interesting, and since I took it along with CS180, there was some overlap between the classes as well. Eskin himself is a super smart guy, but isn't the best lecturer. He often went into detail on advanced topics that weren't important, and didn't have slides for RNA Sequencing even though it wasn't in the textbook. However, the TAs for the course were super helpful and reviewed the material which was super helpful.

The class involved reading small research papers, programming homework problems from the textbook, programming projects, a midterm, and a final. Of those, the homework problems and projects were the most time consuming.

The quarter I took 122 was an experimental quarter: Eskin wants to make the class more difficult since (in his words) "people are doing too well in it". However, for the first 3 projects, the starter code provided by the TAs was good enough for full credit, which was a bit of a joke. Expect this to change in future quarters. One of these projects, sequence alignment on a 100 million length genome was so hard and stressful that they had to make it extra credit. Also, this was the first time they ever had RNA Sequencing projects, so there were some teething troubles with it, but this should get easy in future quarters.

On all projects, the TAs made it seem like they were easier than they actually were (assuming you did it diligently). It helps to start early on the projects and ask the TAs for help.

The exams were fair and easy. They gave out a practice exam which we had to solve and turn in, and the real exams were similar to the practice ones, which was really helpful. The final was non-cumulative as well.

If you're a CS major, you may want to do a little review of biology before you take this class. They jumped straight into the material, and as a result, I was lost for the first couple of weeks. Also, this is a great class if you're interested in bioinformatics research. Talk to him in office hours or after class and if you show some interest, he'll probably take you in.

Overall, it's a pretty chill class apart from 2 of the projects. I'd recommend taking it. The grading is pretty good, too.

Took this class during COVID; the prof and TAs had some weird communication issues where the professor would say something about a due date and the TAs would lag behind a little on getting the news out to all students. They did their best though! Whenever more than a few people asked for an extension, it was given globally to the whole class. Eleazar kept calling these “revolts” jokingly, but they totally were. I don’t think we had a project due until week 6.

All things considered, it was a good class. You learn about genome assembly, resequencing, RNA sequencing in the context of computation. The Stepik homeworks were way more CS heavy than the projects, honestly. They offered a ton of extra credit and lots of cool guest speakers if you’re into research. The projects aren’t that hard and the exams are just there to see if you’re paying attention. If you’re into research/bioinformatics, I’d suggest this as an introductory course. Not too difficult and pretty cool. This is coming from someone who learned Python concurrently with taking this course!