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 2025 - Wow this class was horrible. As cool of a guy ET is, I never want to take a course offered by him again after this. Lectures were so dry and all he did was read over slides containing complicated derivations and equations that were incredibly difficult to follow. The homework assignments were brutal. Basically ALL matlab and super tedious. I would often find myself blindly promoting AI to write code that I barely understoood because the concepts were so tricky. ET was also pretty lazy it seemed. He didn’t post review videos when he said he would, we did have one bonus assignment but this was posted AFTER the final due a week after the quarter ends. The midterm was pretty light but since the class did so well on the midterm he decided to make the final much more difficult because apparently we did too well on the midterm than what he expected. And WOW that final was insanely difficult and frankly quite worrying considering it’s 40% of our grade. It wouldn’t be so bad if we had some handwritten practice before hand. But since all the homework was matlab based and lectures based on equations, we were kinda screwed. Honestly I don’t like hating on professors and at the end of the day it IS possible to do well in this class if you are extremely studious and attend every discussion and lecture and do practice problems on the side to prepare yourself. He does give homework extensions if you ask which is nice and very needed but no late homework is excepted so get started early. The content starts off really easy but builds on itself and can get very complicated forwards the end of the quarter. If ET is teaching this class hold off until someone else like professor Margulis offers it, he’s a much better better lecturer and properly explains the concepts from what I’ve heard.
Spring 2025 - Wow this class was horrible. As cool of a guy ET is, I never want to take a course offered by him again after this. Lectures were so dry and all he did was read over slides containing complicated derivations and equations that were incredibly difficult to follow. The homework assignments were brutal. Basically ALL matlab and super tedious. I would often find myself blindly promoting AI to write code that I barely understoood because the concepts were so tricky. ET was also pretty lazy it seemed. He didn’t post review videos when he said he would, we did have one bonus assignment but this was posted AFTER the final due a week after the quarter ends. The midterm was pretty light but since the class did so well on the midterm he decided to make the final much more difficult because apparently we did too well on the midterm than what he expected. And WOW that final was insanely difficult and frankly quite worrying considering it’s 40% of our grade. It wouldn’t be so bad if we had some handwritten practice before hand. But since all the homework was matlab based and lectures based on equations, we were kinda screwed. Honestly I don’t like hating on professors and at the end of the day it IS possible to do well in this class if you are extremely studious and attend every discussion and lecture and do practice problems on the side to prepare yourself. He does give homework extensions if you ask which is nice and very needed but no late homework is excepted so get started early. The content starts off really easy but builds on itself and can get very complicated forwards the end of the quarter. If ET is teaching this class hold off until someone else like professor Margulis offers it, he’s a much better better lecturer and properly explains the concepts from what I’ve heard.
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