C&EE 103
Applied Numerical Computing and Modeling in Civil and Environmental Engineering
Description: Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course M20 (or Computer Science 31), Mathematics 33B or Mechanical and Aerospace Engineering 82 (either may be taken concurrently). Introduction to numerical computing with specific applications in civil and environmental engineering. Topics include error and computer arithmetic, root finding, curve fitting, numerical integration and differentiation, solution of systems of linear and nonlinear equations, numerical solution of ordinary and partial differential equations. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Spring 2023 - Margulis is a pretty nice guy. His lectures are organized and the slides are well-put-together, but the content itself can be very dry as the class covers iterative/numerical methods of mathematical processes. Overall, the class is very manageable and pretty easy as long as you don't procrastinate on PSETs, collaborate with peers, and do well on the midterm. Even though MATLAB is used a lot, there isn't any actual coding; it's mostly setting up parameters and calling pre-written functions and plotting. The final project is longer and more confusing (so pay attention to the wk 8, 9, 10 topics) but as long as you work on it steadily and meet with the professor/TAs, you should be good.
Spring 2023 - Margulis is a pretty nice guy. His lectures are organized and the slides are well-put-together, but the content itself can be very dry as the class covers iterative/numerical methods of mathematical processes. Overall, the class is very manageable and pretty easy as long as you don't procrastinate on PSETs, collaborate with peers, and do well on the midterm. Even though MATLAB is used a lot, there isn't any actual coding; it's mostly setting up parameters and calling pre-written functions and plotting. The final project is longer and more confusing (so pay attention to the wk 8, 9, 10 topics) but as long as you work on it steadily and meet with the professor/TAs, you should be good.
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Most Helpful Review
Summer 2023 - There are two parts in this class. The theoretical math part and the practical coding part. The total grade is calculated on 7 HWs (10% each) and 1 Final Project (30%). And for homework, half of it is math problems and it includes a lot of manual calculations and few elementary math proofs; the other half is MATLAB coding. The Final Project grade is based on MATLAB coding (70%) and a report (30%). Then, for the theoretical part, the professor gave all resources you can expect as a student, pre-recorded lectures/notes (First half by professor Ertugrul Taciroglu; second half by professor Steve Margulis), recorded live-stream lectures/notes(by professor himself), practice problems with solutions, homework solutions, lot of Office Hours, a very good textbook (most of the time you don't have to read because of other resources); basically, you just learn the theoretical part as much as you want, and a good grade is guaranteed (because the professor does not have a TA and he graded extremely lenient himself, and the theoretical part looks like practice problems). The hard part is the MATLAB coding part. It depends, if you know how to code and use the internet wisely, it should not be a big deal since the professor would provide a template to you. The Final Project is all about coding (70% of Final Project Grade), try to understand "Least-square approximation, all methods of interpolation, all methods for Initial Value Problems (ODE only), the only introduced method of solving nonlinear system, i.e., Newton Iteration very well for Final Project. It's obvious, the person who grades your homework matters, and usually it's not your professor himself, be aware of that. There exist 2% extra credits and 97.5% is A+, 90% is A, 85% is A-; if you really want to explore the world of numerical analysis, I recommend taking it with Professor Rüter.
Summer 2023 - There are two parts in this class. The theoretical math part and the practical coding part. The total grade is calculated on 7 HWs (10% each) and 1 Final Project (30%). And for homework, half of it is math problems and it includes a lot of manual calculations and few elementary math proofs; the other half is MATLAB coding. The Final Project grade is based on MATLAB coding (70%) and a report (30%). Then, for the theoretical part, the professor gave all resources you can expect as a student, pre-recorded lectures/notes (First half by professor Ertugrul Taciroglu; second half by professor Steve Margulis), recorded live-stream lectures/notes(by professor himself), practice problems with solutions, homework solutions, lot of Office Hours, a very good textbook (most of the time you don't have to read because of other resources); basically, you just learn the theoretical part as much as you want, and a good grade is guaranteed (because the professor does not have a TA and he graded extremely lenient himself, and the theoretical part looks like practice problems). The hard part is the MATLAB coding part. It depends, if you know how to code and use the internet wisely, it should not be a big deal since the professor would provide a template to you. The Final Project is all about coding (70% of Final Project Grade), try to understand "Least-square approximation, all methods of interpolation, all methods for Initial Value Problems (ODE only), the only introduced method of solving nonlinear system, i.e., Newton Iteration very well for Final Project. It's obvious, the person who grades your homework matters, and usually it's not your professor himself, be aware of that. There exist 2% extra credits and 97.5% is A+, 90% is A, 85% is A-; if you really want to explore the world of numerical analysis, I recommend taking it with Professor Rüter.
Most Helpful Review
Spring 2023 - This was one of the most challenging C&EE classes I've taken at UCLA. His midterm was lightwork with the class average being an A- but his final was outrageously difficult that most people didn't finish the final and wrote gibberish to scavenge as many points as possible. The MATLAB assignments were insanely difficult and long that my friends and I used Claude AI or ChatGPT to finish within a reasonable amount of time. For the midterm, STUDY the practice midterm but the practice final was useless.
Spring 2023 - This was one of the most challenging C&EE classes I've taken at UCLA. His midterm was lightwork with the class average being an A- but his final was outrageously difficult that most people didn't finish the final and wrote gibberish to scavenge as many points as possible. The MATLAB assignments were insanely difficult and long that my friends and I used Claude AI or ChatGPT to finish within a reasonable amount of time. For the midterm, STUDY the practice midterm but the practice final was useless.
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