COM SCI 161
Fundamentals of Artificial Intelligence
Description: Lecture, four hours; laboratory, two hours; outside study, six hours. Enforced requisite: course 180. Introduction to fundamental problem solving and knowledge representation paradigms of artificial intelligence. Introduction to Lisp with regular programming assignments. State-space and problem reduction methods, brute-force and heuristic search, planning techniques, two-player games. Knowledge structures including predicate logic, production systems, semantic nets and primitives, frames, scripts. Special topics in natural language processing, expert systems, vision, and parallel architectures. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Spring 2020 - TAKE HIS CLASS! Professor Darwiche is an absolute gem! I got into the class on a last-minute PTE after spring quarter went remote. He has to be one of the most well-adjusted professors out of all of UCLA's remote courses. From day one, he has been prepared and well-versed with the Sketchbook app to use as a whiteboard (great handwriting too), rarely had tech problems, edited *ALL* of the recorded lectures to correct mistakes on screen and cut out any pauses/wait time. He divided the videos into 2 parts to upload, each 35-40 minutes long, which made it super easy for us to find things when rewatching. Even went to lengths to add his own intro music for the videos and sometimes draws a little daisy on the first slide :') He always stuck around after lecture to answer students' questions and provided external resources (optional) if you were interested in reading more. He's very patient, used engaging and funny examples, and explained concepts SO well. This was not a class where I had to often re-watch lectures or read the textbook to catch up. Exam was open book and pretty manageable, exactly what you'd expect based on lecture and homework material. TA's were also very knowledgeable and helpful in discussion (Shirley was great!) There's roughly one homework per week, usually takes less than 4 hours. I already knew Darwiche was a beloved and highly-regarded professor before enrolling his class, but in contrast to how other professors are handling remote instruction, Darwiche is miles ahead and definitely went above and beyond to make sure students are getting the best out of this course. Really wish I can take another class with him some day!
Spring 2020 - TAKE HIS CLASS! Professor Darwiche is an absolute gem! I got into the class on a last-minute PTE after spring quarter went remote. He has to be one of the most well-adjusted professors out of all of UCLA's remote courses. From day one, he has been prepared and well-versed with the Sketchbook app to use as a whiteboard (great handwriting too), rarely had tech problems, edited *ALL* of the recorded lectures to correct mistakes on screen and cut out any pauses/wait time. He divided the videos into 2 parts to upload, each 35-40 minutes long, which made it super easy for us to find things when rewatching. Even went to lengths to add his own intro music for the videos and sometimes draws a little daisy on the first slide :') He always stuck around after lecture to answer students' questions and provided external resources (optional) if you were interested in reading more. He's very patient, used engaging and funny examples, and explained concepts SO well. This was not a class where I had to often re-watch lectures or read the textbook to catch up. Exam was open book and pretty manageable, exactly what you'd expect based on lecture and homework material. TA's were also very knowledgeable and helpful in discussion (Shirley was great!) There's roughly one homework per week, usually takes less than 4 hours. I already knew Darwiche was a beloved and highly-regarded professor before enrolling his class, but in contrast to how other professors are handling remote instruction, Darwiche is miles ahead and definitely went above and beyond to make sure students are getting the best out of this course. Really wish I can take another class with him some day!
Most Helpful Review
Had Dyer for a 8 AM class... that's right, a freakin' 2-hour lecture on AI at EIGHT IN THE MORNING. That does not help in staying up during is lectures, which are usually pretty disorienting and hard to follow as he likes to go off on little tangents and mostly irrelevant anecdotes fairly often. Projects are time-consuming but not impossible, provided you have a good TA (which I was fortunate to have). However, they're basically LISP exercises almost completely irrelevant to the material he actually goes over. The biggest minus in his class is his extremely long exams that no one can finish... while the final is not cumulative, both his midterm and final are super long, closed book and closed NOTES. This doesn't work well too well when coupled with the fact that he tries to pretty much go over the entire textbook in one quarter. Each exam roughly covers at least 10 chapters' worth of material, and unless you go to all of his 8 AM lectures and stay up through them and/or read the entire textbook yourself, well... good luck with that.
Had Dyer for a 8 AM class... that's right, a freakin' 2-hour lecture on AI at EIGHT IN THE MORNING. That does not help in staying up during is lectures, which are usually pretty disorienting and hard to follow as he likes to go off on little tangents and mostly irrelevant anecdotes fairly often. Projects are time-consuming but not impossible, provided you have a good TA (which I was fortunate to have). However, they're basically LISP exercises almost completely irrelevant to the material he actually goes over. The biggest minus in his class is his extremely long exams that no one can finish... while the final is not cumulative, both his midterm and final are super long, closed book and closed NOTES. This doesn't work well too well when coupled with the fact that he tries to pretty much go over the entire textbook in one quarter. Each exam roughly covers at least 10 chapters' worth of material, and unless you go to all of his 8 AM lectures and stay up through them and/or read the entire textbook yourself, well... good luck with that.
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Most Helpful Review
Winter 2019 - I can see where the negative reviews come from regarding the course content since ppl would expect AI courses to be modern and fun instead of theories. While I agree with that, I do want to add my personal thoughts regarding the problem. There are also other professors besides prof. Gu who teach this course and cs department requires them to teach the same materials (otherwise it would be unfair for both teachers and students in different quarters). this intro level AI course was designed years ago and ofc it is a little outdated, but the content can hardly be changed unless the department decides to. I guess for ppl complaining here, it would be better if you talk to cs dept directly instead of giving a low rating for some professors... Regarding the professor, I took the course when the pandemic hit in 2020 and everything was a mess. I think the professor is knowledgeable and cared a lot about course quality and did a great job accommodating students' needs. I do agree that sometimes the slides are too brief and the textbook definitely gives a more thorough explanation. BUT that is based on if you don't listen to the lecture at all and just reading the slides. Based on my personal experience, it is easier to understand the materials when I went to the lecture with professor's demo. For TAs, I would agree that they were not that helpful comparing with TAs from other courses. but I do not think they were being lazy (at least mine wasn't) Their speaking skills are not too good so it's difficult to understand, but they were willing to stay after discussion with me to make sure my concerns were resolved. The HWs and tests are doable as other comments said. In general, I think this course is a descent intro-level AI course that shows/prepares you the fundamentals behind the fancy side of AI/ML. I also consider it as a good elective with very manageable workload and easy A.
Winter 2019 - I can see where the negative reviews come from regarding the course content since ppl would expect AI courses to be modern and fun instead of theories. While I agree with that, I do want to add my personal thoughts regarding the problem. There are also other professors besides prof. Gu who teach this course and cs department requires them to teach the same materials (otherwise it would be unfair for both teachers and students in different quarters). this intro level AI course was designed years ago and ofc it is a little outdated, but the content can hardly be changed unless the department decides to. I guess for ppl complaining here, it would be better if you talk to cs dept directly instead of giving a low rating for some professors... Regarding the professor, I took the course when the pandemic hit in 2020 and everything was a mess. I think the professor is knowledgeable and cared a lot about course quality and did a great job accommodating students' needs. I do agree that sometimes the slides are too brief and the textbook definitely gives a more thorough explanation. BUT that is based on if you don't listen to the lecture at all and just reading the slides. Based on my personal experience, it is easier to understand the materials when I went to the lecture with professor's demo. For TAs, I would agree that they were not that helpful comparing with TAs from other courses. but I do not think they were being lazy (at least mine wasn't) Their speaking skills are not too good so it's difficult to understand, but they were willing to stay after discussion with me to make sure my concerns were resolved. The HWs and tests are doable as other comments said. In general, I think this course is a descent intro-level AI course that shows/prepares you the fundamentals behind the fancy side of AI/ML. I also consider it as a good elective with very manageable workload and easy A.
Most Helpful Review
Professor: + Trying to be funny, while not funny. + Slow pace through the lecture. Project: project is very boring. Check out UC Berkeley AI class, they do Pac Man Ai bot. Then they even compete in tournament. If you took CS 161 with this professor, you don't get to do this. Midterm and Final: The only thing I got to complain is that the space he left to answer each question is so SMALL. I don't recall, he allows to use additional paper to write down the answer.
Professor: + Trying to be funny, while not funny. + Slow pace through the lecture. Project: project is very boring. Check out UC Berkeley AI class, they do Pac Man Ai bot. Then they even compete in tournament. If you took CS 161 with this professor, you don't get to do this. Midterm and Final: The only thing I got to complain is that the space he left to answer each question is so SMALL. I don't recall, he allows to use additional paper to write down the answer.
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Most Helpful Review
Fall 2020 - During the Covid Era, This professor decided to prerecord his lectures weekly and post them at the scheduled lecture time, then have a weekly office hours of sorts, where you can go and ask questions after lecture. It definitely worked well for a while, but I found that the q/a sessions would be less and less helpful as time went on. The LISP projects are seemingly required by the department for the class, and just feel outdated and untouched. However, they will give you great functional programming practice that will help you in cs131. Tests are very concept based, and the homework projects/lecture videos will not help you, you will need to read the book for the details needed to answer the test questions. He is a good professor but I cant help but feel like we wasted a lot of time in the class focusing on logic as taught in Phil 31, and search algorithms as taught in cs180.
Fall 2020 - During the Covid Era, This professor decided to prerecord his lectures weekly and post them at the scheduled lecture time, then have a weekly office hours of sorts, where you can go and ask questions after lecture. It definitely worked well for a while, but I found that the q/a sessions would be less and less helpful as time went on. The LISP projects are seemingly required by the department for the class, and just feel outdated and untouched. However, they will give you great functional programming practice that will help you in cs131. Tests are very concept based, and the homework projects/lecture videos will not help you, you will need to read the book for the details needed to answer the test questions. He is a good professor but I cant help but feel like we wasted a lot of time in the class focusing on logic as taught in Phil 31, and search algorithms as taught in cs180.
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