Anyone who had the unfortunate opportunity to take CS 33 with Eggert will find that CS 131 with him is easier.

But not that easy.

This class crams a ton of programming languages into 10 weeks and expects you to learn them as if you only had this one class for the quarter. Be prepared to slam your head against the wall while doing Homework 2 (the hardest one by far) and spend a lot of hours dissecting the textbook (it's helpful, but dense) to actually learn the material.

For lectures, Eggert invites you to his two-hour TedTalks twice a week. He's a great lecturer if you just wanted to sit in on his history lessons and hear his opinions on language semantics or something. But if you actually want to learn to pass the class, please go to your TAs.

Assignments take forever, but Eggert has that incredibly generous late policy, so make sure to take advantage of it. TAs are a godsend in this class (shoutout to Patricia for spending a whole night writing test scripts for the Python project during Thanksgiving break! <3). Anyways, go to office hours and ask questions on Piazza. Your grade depends on it if you aren't a natural CS whiz.

Exams are hard. Seriously, the average for the midterm was like 45%. And the final will probably be in that range too. There's no way to truly study for Eggert exams. But it's an even playing field because almost everyone is just as confused! Eggert knows people are always lost in his class. He grades on knowledge, but he rewards INTUITION. No matter how wrong your answer may be, if you can back it up with any kind of evidence, you will get partial points. Pro-tip: Eggert's favorite questions in this class are language implementations and optimization languages. Is X language better than Y language for Z task? Is it feasible to implement X's function in Y to do Z?

Lastly, do yourself a favor and do NOT take this class with CS 111. You will die. Literally. I took this course in a four-class quarter and it was not fun to say the least. But everything will be all right. Getting through Eggert is like a rite of passage. You can't call yourself a true CS major without getting Egged after all.

WORST OF ALL TIME

I'm prepared for heavy assignments and difficult tests on things he barely lectured in class. However, what I want to tell people right now is his unreasonable, mysterious curve and final grading strategy. The final grading is messy, with some people curved down but some not, just because he thought we would take benefits from generous graders in assignments. He didn't even tell which portion of the class was curved down and how, nor did he seem to consider that some answers might just be good enough to receive a full grade from any grader. It has NO transparency at all. You never know if you would be mysteriously curved down at the deadline of final grade submission day, and you can do nothing about it (since he will also not expose how he did it). I got full grades for every assignment, but if I knew those grades does not reflect anything, I would consider P/NP instead of getting this shitty grade that ruins my GPA (never got a B before).

In a nutshell, he is not the type of professor we usually met that gives you a hard time during the quarter but curve up at the end to make students learn. He is the devil that gives people a hard time till the moment you get your final grade. I don't know how curving down without clear explanation benefits learning, and he might not care.

This class was a complete mess in Winter 2021. There was only one TA who seemed to care- thank you Boyan Ding.

The workload was so high that the TAs could not keep up with grading and gave arbitrary scores to everyone on HW5 and HW6. For example, I turned in HW5 6 days late (-32 penalty) but got a 100.

If Eggert cares about most of the students learning, rather than only the top 5 or 10% of the class learning, he should make the workload lighter by removing a HW or two, or at the very least simplifying HW2 and HW5.

Shout out to Ian Sommervill. Congratulations for writing the most boring textbook I've read in my life.

Eggert is Eggert, just pray for not getting egged on the exams.

Lectures always come after assignments so be sure to start googling early! Never wait for the lectures. The lectures are helpful in the sense that they contain a lot of information, but never count on it to help you with any of your assignments. Be sure to find a better discussion session, especially the ones that guides you through assignments. Getting 100 on each assignment is doable but not neccessary since they worth little.

There is a group project to build a full-stack webapp (start early!!!). As long as your app covered the features in the spec and looks beautiful and that your personal contribution (tracked via git history) and report show enough effort you will get full score.

Since this is still an experimental lecture, some important stuff got left out by the end of the quarter, I think professor Eggert will try to fix that next time.

Difficulty levels
Assignment1: Easy
Assignment2: Medium
Assingment3: Easy/Medium
Assignmrnt4: Easy
Assignment5: Hard
Assignment6: Hard
Midterm: Eggert
Final: Eggggggggert (not typo)
Project: medium to hard (your choice)

Haven't gotten grades yet but this class was just awful.

The popular opinion for this course is that the projects are way too hard and take way too long. For most people, that does carry quite a bit of truth. However, just saying that would make this review sound exactly like the ten preceding this one, so I'll try to do better.

I would qualify the difficulty in the projects, as not that they themselves are difficult, but rather they require quite a lot of knowledge and maturity in programming in C – something that the previous Computer Science classes do not prepare the students well for. Having done the projects myself and helped numerous others, I'd say the two major pillars that people were not as prepared for were:

- reading documentation (“man pages”): ability to skip the boilerplate and get to what you are actually looking for; finding and adapting example code

- understanding and applying memory allocation: fixed-size arrays vs. malloc(); pointers, lifetime, and ownership. Most people understand what they are and how they are different, but applying that knowledge correctly could be a different challenge.

If you are or become comfortable with these things, the projects will be quite doable.

On the other hand, the exams had a different focus. I hate to use the overused word, but they force you to think critically and provide a reasoned answer backed up with facts and experience. For dreamers and debaters, it was heaven. For the rest of us, it was a first taste at what software engineering is all about: a whole lotta dreaming and debating. (Oh, feel free to replace “dream” with “BS.”)

But where do you get the facts and the experience? The former you get by following textbook readings, which are unfortunately very heavy, as well as by listening and processing Professor Eggert's excellent lectures. The latter you get by stumbling and reflecting while doing the projects.

Of course, many online resources exist for help in the projects. However, a word of caution if you do decide to go down that route: most folks on GitHub who post their solutions were just as clueless as you are when they did it. Thus there is great variance in the the quality of said resources.

But if you do end up finding resources of high quality, make sure to maximize your learning by carefully reading and understanding why they did something but not something else: because there’s an actual reason, or because they just felt like it? How did they think of something that you didn't? Reflect, and you’d become a much better Computer Scientist or Software Engineer for it.

Probably said too much already, so I'll stop. In any case, good luck, and hope you enjoy the class!

Worst class that I've ever taken. The workload is insane especially for the first 6 weeks. It eases up a tad but then they had the worst assignment ever during week 10 (when the final is on the Sunday before finals week) that was so time consuming and hard that half the class didn't even do it. You're expected to learn pretty much a whole language/aspect of cs (bash, python, c, linking, git) and then complete super time consuming hw assignments showing "mastery" of a concept that you just learned. Also, Eggert doesn't teach the class. The TAs do, so if you get a bad TA then you're screwed. The only good thing about this class is the generous late policy. The final exam was terrible and scarring. I never want to take this class again and I never want to take an Eggert exam either. This class needs to be reworked. The workload can be cut in half easily especially for a 3 unit class. I made the mistake of taking this at the same time as CS 33 and the workload was insane. Worst quarter at ucla so far. I have no clue how I scraped out with a B but I don't want to think about this class anymore.

I'm hesitant to post a review for this class because you really don't have a choice on who to take it with since Eggert is the only professor that has taught it in recent memory.

130 is kind of a crappy class. Not at all difficult, just crappy. Tons of assigned reading and quizzes every class. Eventually you learn to ignore the readings and just fake it on the quizzes since they aren't worth much of your grade. The project is worth 40% of your grade, and with our client it was pretty easy (definitely doable in a hackathon context, so not overly time consuming considering you have 5-7 people on the team). The Midterm and Final are open book and open notes, but if you take notes on this class you will probably want to kill yourself, and you are already ignoring the reading assignments, so your best bet is to get someone to make a copy of their class notes for you and borrow some poor sucker's copy of the books (or use your free/cheap printing to print the PDFs that are easy to find with a google search).

At the first lecture the class is billed as one of the most useful classes you will take. I'll let you decide for yourself, but I don't believe it.

If you have to take this class, buckle up because, in my 2 years here, it has given me the most workload of any class by far.
Eggert himself is pretty friendly and a super engaging lecturer. His lectures sound like TED talks, and I never found myself dozing off in his class. He is very intelligent, and I respect him as a software engineer. You will need to show up to lectures to do well on the exams because, for certain questions, he might allude to random points he makes during lectures.
Speaking of the exams, they are notoriously difficult and there's not much you can do to study for them. The exams are conceptual and expect you to have mastered the material. Most people end up printing the entirety of their notes, myself included, which can help for 1 or 2 questions. The best way to study is to go over previous exams and the LA practice exams.
Another major part of the class is the homework/labs. Eggert's late policy is very generous, but my advice is to only use it when you need to and just start the assignments early. You'll need the time. Google is your best friend here.
You also have a final project where you create a full-stack web app, usually in a group of 5. If this is starting to sound like a lot of work, that's because it is. In my opinion, this is the most rewarding part of the class, but I encourage you to meet people early in the class and group up with people you trust. I made the mistake of grouping with randos, and maybe I'm just unlucky but none of them wrote a single line of code. So I spent every day from Friday Week 8 to Wednesday Week 10 working on this damn project.
Similar to other reviews, I was disappointed with the lack of transparency and the obscene delays in grading. One of our assignments was due Week 4-5 but was returned a few days before grades were due. It took a toll on my mental health stressing over these grades, and looking back I should have just accepted that I get what I get. I don't understand how the curve works, but I'm pretty sure he goes for a B/B- average.
Overall, you will learn a lot, but know what you're getting yourself into.