This class is as easy or difficult as you would like it to be. Although most people who took CS32 and did reasonably OK would get a good grade in this class, I would suggest taking it only if you are interested in exploring bioinformatics and not just for a good grade.

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.

*grabs you personally by the throat* SAVE YOUR SOUL. DO NOT TAKE THIS COURSE.

Unless you want to do 4 projects that have very little guidance in the specs, each split into 2 parts that require different types of outputs, on top of doing 7 homeworks, each with 4-10 Leetcode-like coding problems evaluated on a shitty $80 online textbook website (Stepik) where you have to download the input to your computer, run the code, and upload the outputs and pray that you matched the formatting exactly, otherwise repeat the process. (Also, I get Stepik advertising emails in Russian, which 1) I did not sign up for 2) I don't know Russian.)

And about those projects, they decided to try something new this quarter: making us upload our results to a bioinformatics leaderboard website. The fun thing is that 1) They don't post the leaderboard until 2-3 days before the project is due. 2) Someone has to manually approve that you can join the leaderboard. Which means you wait for some poor TA to handle your request. 3) They don't post the grading thresholds WITH the project spec or even when they post the leaderboards sometimes, so if you finish your code early, you have to wait for the announcement of the threshold. If you don't pass it? Guess you're working on the project again!

I have never taken a class with this many Canvas announcements about project extensions and grading thresholds and about homework problems becoming Extra Credit because very few people are successfully solving it. And have I mentioned that they also made us read 4 papers and ask and answer other students' questions about it? To me, it felt like the blind leading the blind.

The only saving grace of this course is that the midterm was reasonable. If you read and understand the textbook and the slides (which is what I did because their lecturing is Pretty Bad, especially Ernst's), you can do the problems. They just make you apply the techniques to the given data. They also gave a set of practice problems that matched pretty closely. I'm writing this review before the final though, so maybe they decide to completely switch it up on us. (But, I'm skimming the final practice problems, it seems like it's the same problem format.)

Who knows. Maybe you'll enjoy the torture more than I did. Maybe you're that kid who was already working on a bioinformatics library for their research and used it for Project 1, landing you a score in the top 3, at which point you're obligated to do a presentation of your solution to the class. The class is mostly empty, by the way. Just like how this class made me feel.

Grade breakdown for Spring 2023: Projects 25%. Homeworks 20%. Midterm Exam 25%. Final Exam 25%. Paper/Guest Speaker Question and Responses 5%.

Standard seminar class that's required for any CASB major/minor. Show up, take some brief notes, and write a review for each talk. The review is just a summary of the talk, the most recent developments, what you didn't understand, and feedback. Some of the talks were actually really cool and prompted several students to join the researchers' labs (my favorites were Neuroimaging Informatics, AI in Medicine, and Genetic & Phenotypic Psychiatry), but expect them to change year by year. If you're already in a lab and like the research you're doing, it's pretty boring, but there's practically no workload - if you sit at the back of the lecture hall, you will see a bunch of people doing homework, solving the NYT crossword, playing snake, or chatting while taking notes lol

The slightly annoying part was trying to summarize a boring talk that didn't make any sense, since some researchers assume that undergrads have a working knowledge of a bunch of statistics and ML stuff from the stats 100 or 101 series. But, even if you have a big-picture understanding and can at least name the methods they used without explaining then you're fine. Also I kinda hate genetics and like 70% of them were about it so that was also pretty annoying.

The bioinformatics classes seem to change a lot from quarter to quarter, but here is Spring 2023.

Pros:
- Lectures are not necessary to do well.
- Lectures, tests, homework, projects, and papers all synergize together extremely well. You can watch a lecture about an algorithm, read the paper they give you that describes it, work out individual subroutines on the homework, and put it together on the project. I didn't figure that out until later, but it's pretty special.
- You feel like you learned something hard and useful.
- Opportunities for extra credit or easy points.
- Very easy tests.

Cons:
- A constant barrage of work from beginning to end. The sheer volume and difficulty of the homework and projects is incredible. For reference, the final project of CS CM121 was to align sequencing reads to a small genome and find what genotype it had at a specific point in the genome. Since the genome wasn't that long, you were just supposed to brute-force align a bunch of reads and use Bayes Theorem to find the most likely genotype. For CM122, the FIRST project of 4 or 5 projects was to do the same, but with a genome millions to a billion bases long with mutations. You have to employ a very interesting fast substring search algorithm to do that and figure out a way to account for frameshift mutations. I learned to tell my Mac to stay awake while it was closed so I could run the algorithms overnight.
- Feedback is hard to come by, especially for the homework. Each homework question asks you to write a function and test it with some sample input before running it with the question's input. I can't count how many times my code worked with the sample but not the graded input and I had no idea why.

I think they should get rid of 121 and spread this class over the two quarters.

This class seems really bad until you realize that the exams are almost one to one copies of the practice exams (at least they were for spring '23). I glanced over the practice midterm and to my surprise when I took the actual midterm it was basically the exact same with different numbers. From then on I did not go to a single lecture, partly because they were really bad and hard to follow. All I did was study the practice final and ended up getting a 100 on the actual one. The issue is that the workload in this class is actually insane: weekly homework + weekly projects + discussion posts. It does however become manageable once you realize you don't have to go to lecture. I would recommend going to discussion and office hours for help on the projects and homework, particularly because the platform the homework was conducted on was atrocious. They also did some unreal grade rounding at the end. Based on the grade break down in the rubric I calculated I would get around a D- but somehow ended up with a B-. Considering I barely did discussion posts and only completed a little more than half the homework and projects I'd say this class is pretty easy to get a good grade.

I hated this class. I can't say too much about the grading and the exams because I dropped the course before the first midterm. But if you are just a CS(-related) major without any interest or background in biology, be VERY careful taking this course. I personally had a hard time especially since they reworked the course. As I heard, the projects used to be guided with template code to work with, but Spring 2023 did not receive ANY of that. The Stepik assignments were extremely challenging and draining, especially if you aren't experienced in Leetcode, and you are completely on your own figuring out how to do the projects. I literally could not figure it out and the TAs I asked were so vague so I dropped before even finishing Project 1a.

Strangely, they recorded every class but did not post them. You had to have a legitimate reason to get the recordings and you'd email them for it.

Don't let the grading fool you into thinking this is a grade-safe elective, either. The class is cross-listed for graduates as well so I'm assuming that's where the higher portion of grades come from.

There is very little hand-holding and you need to figure out a lot on your own, especially if you are just coming from CS 32 and that's all the programming experience you've had. Unless you are in love with bioinformatics and would be okay dedicating all your free time to self-learning this course from the ground up, please DO NOT TAKE THIS CLASS!

CS CM124 Winter 2013

Prof is a nice guy... really relaxed and if you need help just go to him or the TA.

The class isn't too demanding, but if you want to work more on the final project you can always make it more challenging for yourself.

HW/MT/Final are just there to show you kinda whats going on.. the TA helps you through all of them during discussions. And by helps you through them i mean walks you through the problems, and solutions. Lectures/Discussions are all filmed and posted, which is nice.

Final Project: For this quarter, he gave us a list of projects to pick from, and corresponding difficulty levels. If you dont have much time or dont really feel like you know whats going on, just pick an easy one... and if you get the hang of it you can add more to the project to challenge yourself. The project is the majority of the grade, i believe. For future classes he said he might mix it up, but probably similar stuff (pick your own language to code in, etc).

There is a presentation for the project at the end of the quarter. 10 min of explain what you did. Not coding details.. just the big picture and your results like accuracy and run time. Kinda strange.. but you vote on your classmates via text. Not sure if this actually affects the grade, but you get participation for doing it.

Interesting peak into a different side of CS.. i'd recommend the class. Not hard, good prof, not too stressful... and you learn along the way.

THIS IS NOT A COMPUTER SCIENCE CLASS. It's nearly all statistics. This class is terrible and should be avoided. Eskin is an awful professor; he does tell you exactly what you need to know for tests, but he clearly doesn't care about his job and doesn't care if students learn anything or enjoy the class at all. Multiple times he would say in lecture "why am I even here teaching? You guys are gonna forget this all in a few weeks anyway."
Also, we were expected to know Python or R coming into this class. The TA (Michael, the worst TA I've ever had by far) told us in the week 1 discussion that if we didn't know those languages, start teaching ourselves. The homeworks (we had four programming assignments) are easy if you know Python/R, and extremely difficult if you aren't familiar with those languages. Besides those homework assignments, WE NEVER TOUCHED PROGRAMS IN THIS CLASS (and no, they don't talk about Python/R in lecture at all). 95% of the class is statistics and math, which was not what I was expecting (or prepared for).
The syllabus is straight up ignored. The TA consistently showed up 15 minutes late to discussion, and sometimes didn't show at all and forgot to send us a cancellation email. I didn't even know where the office hours were until maybe week 4, just because they never talked about it and didn't put the location on the syllabus.
tl;dr: This class is a pretty easy A but you will not learn anything (unless you're super interested in extremely difficult statistics and can keep up with the professor). There is very little CS involved, and Eskin and the TA don't care about the students at all.

This class is more of an advanced stats class. The math that the professor went through in the lecture is super hard. Python and R are the preferred programming tools. However, I do see some students using C++ and still be able to get full credits on all the assignment. Basically, as long as you understand the math behind the " model" or the "algorithm", the programming assignment is a breeze. TAs and the professor are super helpful if you are willing to talk to them after the class. Though the office hour and the discussion may not be as "formal" as other upper div CS courses (mentioned in other reviews), TAs are always in the Zarlab (in the second floor of MS building) and almost always available. The basic idea is to really let us learn as may advance topics as possible. it's okay if you are not fully understanding the material. TAs don't quite get the ideas sometime. THE GRADING IS SUPER GOOD. Strongly recommended if you are interested in bioinformatic.