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Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
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Everything you've heard about this class is true. The homeworks are awful and nearly impossible to do. The exams are the hardest things you've seen in your life and even Eggert talks about how this class has way more work than you should expect.
Now, even after saying all of this, I have learned so much from this one class and I think I would still take this again especially since it felt so rewarding after I was done.
Now, here is my unsolicited advice on how you can do well in this class. The breakdown was: 24% Homeworks (each 4%), 8% Project, 24% Midterm, 44% Final
The very first thing I recommend doing is starting the homeworks early. Literally the day or the day after they get out. If you're able to stay on top of them and finish them a few days before they're due, then you'll do great in this class. Don't be afraid to ask the TA's for help and make sure you understand the rationale and reasoning on why things are the way they are.
When you eventually fall behind, don't be afraid to just turn in an unfinished homework. It's honestly worse to take the late days because the work just starts pilling up so quickly and coding with deadlines is never a good idea. Given that, it is super important that you get the basic idea of what you would have needed to do (and why you need to do it like that) even if you don't get it working.
For the Project, spend as much time as you can on this. Test your code and make sure that your report is really good. There are a lot of edge cases that are not explained. Check Piazza, so you can keep up to date with the various edge cases people think of because you won't get all of them.
Now, for the Midterm/Final, to add on to what everyone else says, I would also recommend studying by trying to connect the various topics he talks about. For example, think about Garbage Collection methods and the issues that could arise if Java used Python's Garbage Collection. Overall, I studied by trying to connect the topics when I was writing my study guide(had to make 2) and then looking at a few practice exams to see if I knew how to approach it. I was able to do really well on the final and average on the midterm
Good luck to whoever read all of this, you're going to need it
how could this guy keep lecturing in such a prestigious school?
it really hurts me that I'm paying about thousands of dollars just to take this kind of shitty, fucked up class.
getting rid of professors like this would be the first step to develop this school.
FUCK YOU EGGERT
This class is hard as hell. Eggert is an incredibly smart man, and a very good lecturer. But he's a pretty tough professor. Exams are classic Eggert, I think both our midterm and final averages were around 45%, obviously with a hefty curve (although very non-transparent since it only happens for the final grade, so I had no idea what grade to expect until it was posted). The assignments are tough, with low means as well. Projects 2 and 5 are the classic hard ones, but 3 was definitely the hardest for me. 1 4 and 6 are much easier. There is thankfully a very generous late policy, as with all of his classes. TA discussions are crucial to success on the assignments and exams. Overall, the class was very difficult, but I definitely learned a LOT about programming languages, which is the goal of the course. But be prepared for a tough quarter if you're taking this class. I didn't really enjoy it during the quarter, but in hindsight, I'm grateful to have learned so much and to have been exposed to a lot of new ideas and ways of thinking.
Just an average CS guy but this class almost had me drop out of college. My only motivation at time was only because I'm so close to graduating
Pretty much like all the other reviews have already said.
Don't take this class, but obviously you have to take it so take it. You'll get through it fine.
Bad. I don't know what I learned and I don't know what I'm looking at when he's drawing diagrams. The only good parts of lecture is when he shares his personal anecdotes or is funny. If you've already taken 111, workload-wise this class is not as bad; the projects are way shorter than 111. Taking 161 is also helpful because Lisp is similar to the languages you have to pick up in this class.
This is the most pointless and unreasonably tough courses I have taken at UCLA. You will teach yourself 90% of the material. The projects, with the exception of hw1,hw4, and the project, are all unreasonably difficult and convoluted, and really, nobody knows whats happening and you can bet that tons of students in the course are githubbing most of the hard parts. The exams are written the night before, as stated by the professor, and the averages can wildly vary from 50%-70%. Make sure you read the book and/or review lecture to perform as well as one can on his exams. As usual with eggert you can expect a fat curve at the end but its never consistent so you cant rely on it. FWIW, when I calculated my raw grade with all assignments/exams graded I had a 59.9, and came out with a C .
Everything you've heard about this class is true. The homeworks are awful and nearly impossible to do. The exams are the hardest things you've seen in your life and even Eggert talks about how this class has way more work than you should expect.
Now, even after saying all of this, I have learned so much from this one class and I think I would still take this again especially since it felt so rewarding after I was done.
Now, here is my unsolicited advice on how you can do well in this class. The breakdown was: 24% Homeworks (each 4%), 8% Project, 24% Midterm, 44% Final
The very first thing I recommend doing is starting the homeworks early. Literally the day or the day after they get out. If you're able to stay on top of them and finish them a few days before they're due, then you'll do great in this class. Don't be afraid to ask the TA's for help and make sure you understand the rationale and reasoning on why things are the way they are.
When you eventually fall behind, don't be afraid to just turn in an unfinished homework. It's honestly worse to take the late days because the work just starts pilling up so quickly and coding with deadlines is never a good idea. Given that, it is super important that you get the basic idea of what you would have needed to do (and why you need to do it like that) even if you don't get it working.
For the Project, spend as much time as you can on this. Test your code and make sure that your report is really good. There are a lot of edge cases that are not explained. Check Piazza, so you can keep up to date with the various edge cases people think of because you won't get all of them.
Now, for the Midterm/Final, to add on to what everyone else says, I would also recommend studying by trying to connect the various topics he talks about. For example, think about Garbage Collection methods and the issues that could arise if Java used Python's Garbage Collection. Overall, I studied by trying to connect the topics when I was writing my study guide(had to make 2) and then looking at a few practice exams to see if I knew how to approach it. I was able to do really well on the final and average on the midterm
Good luck to whoever read all of this, you're going to need it
how could this guy keep lecturing in such a prestigious school?
it really hurts me that I'm paying about thousands of dollars just to take this kind of shitty, fucked up class.
getting rid of professors like this would be the first step to develop this school.
FUCK YOU EGGERT
This class is hard as hell. Eggert is an incredibly smart man, and a very good lecturer. But he's a pretty tough professor. Exams are classic Eggert, I think both our midterm and final averages were around 45%, obviously with a hefty curve (although very non-transparent since it only happens for the final grade, so I had no idea what grade to expect until it was posted). The assignments are tough, with low means as well. Projects 2 and 5 are the classic hard ones, but 3 was definitely the hardest for me. 1 4 and 6 are much easier. There is thankfully a very generous late policy, as with all of his classes. TA discussions are crucial to success on the assignments and exams. Overall, the class was very difficult, but I definitely learned a LOT about programming languages, which is the goal of the course. But be prepared for a tough quarter if you're taking this class. I didn't really enjoy it during the quarter, but in hindsight, I'm grateful to have learned so much and to have been exposed to a lot of new ideas and ways of thinking.
Just an average CS guy but this class almost had me drop out of college. My only motivation at time was only because I'm so close to graduating
Pretty much like all the other reviews have already said.
Don't take this class, but obviously you have to take it so take it. You'll get through it fine.
Bad. I don't know what I learned and I don't know what I'm looking at when he's drawing diagrams. The only good parts of lecture is when he shares his personal anecdotes or is funny. If you've already taken 111, workload-wise this class is not as bad; the projects are way shorter than 111. Taking 161 is also helpful because Lisp is similar to the languages you have to pick up in this class.
This is the most pointless and unreasonably tough courses I have taken at UCLA. You will teach yourself 90% of the material. The projects, with the exception of hw1,hw4, and the project, are all unreasonably difficult and convoluted, and really, nobody knows whats happening and you can bet that tons of students in the course are githubbing most of the hard parts. The exams are written the night before, as stated by the professor, and the averages can wildly vary from 50%-70%. Make sure you read the book and/or review lecture to perform as well as one can on his exams. As usual with eggert you can expect a fat curve at the end but its never consistent so you cant rely on it. FWIW, when I calculated my raw grade with all assignments/exams graded I had a 59.9, and came out with a C .
Based on 86 Users
TOP TAGS
- Tough Tests (31)
- Engaging Lectures (25)