BIOENGR 175
Machine Learning and Data-Driven Modeling in Bioengineering
Description: (Formerly numbered C175.) Lecture, four hours; laboratory, two hours; outside study, six hours. Requisites: Civil Engineering M20 or Mechanical and Aerospace Engineering M20 or Computer Science 31, Mathematics 32B, 33A. Overview of foundational data analysis and machine-learning methods in bioengineering, focusing on how these techniques can be applied to interpret experimental observations. Topics include probabilities, distributions, cross-validation, analysis of variance, reproducible computational workflows, dimensionality reduction, regression, hidden Markov models, and clustering. Students gain theoretical and practical knowledge of data analysis and machine-learning methods relevant to bioengineering. Application of these methods to experimental data from bioengineering studies. Students become sufficiently familiar with these techniques to design studies incorporating such analyses, execute analysis, and work in teams using similar approaches, and ensure correctness of their results. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2024 - Logistics: About 10 quizzes (two attempts, takes the average) 6 Lab assignments 1 Midterm 1 final project (can be solo or in group) Participation grade This class is very interesting and also very useful however it is very poorly organized. Professor Meyer is very sweet and always tries to help you (especially via Slack) however this class is very confusing and the Labs/HWs are very disconnected from the lecture. He also doesn't provide the best examples for the topics covered and can't break down bigger concepts into smaller ones. I personally thought the TAs did a much better job at explaining and breaking down the concepts. It also helps a lot if you have taken a stat class before. Although this class isn't a coding class, coding in Python is a big part of this class and I struggled a lot with implementing different Machine Learning models just because I had never seen how to implement one, in addition the questions are very confusingly worded and you have no idea what the question wants you to do. Make sure to attend EVERY SINGLE OFFICE HOUR, every minute you go to the office hour is an hour you save being confused on the labs. The TAs and professor are very helpful in clarifying what the question wants and helping you with the coding aspect. Discussions are helpful but the TAs just don't have enough time to cover lecture material and help with Labs. It would have been much more beneficial if this class was broken into a lecture and a lab portion. The midterm isn't too bad as long as you do all the previous midterms and get used to his style of asking questions as he generally asks the same types of questions every year. Overall this class isn't difficult topic-wise but extremely time-consuming just because of how confusing everything is so make sure to leave enough time.
Winter 2024 - Logistics: About 10 quizzes (two attempts, takes the average) 6 Lab assignments 1 Midterm 1 final project (can be solo or in group) Participation grade This class is very interesting and also very useful however it is very poorly organized. Professor Meyer is very sweet and always tries to help you (especially via Slack) however this class is very confusing and the Labs/HWs are very disconnected from the lecture. He also doesn't provide the best examples for the topics covered and can't break down bigger concepts into smaller ones. I personally thought the TAs did a much better job at explaining and breaking down the concepts. It also helps a lot if you have taken a stat class before. Although this class isn't a coding class, coding in Python is a big part of this class and I struggled a lot with implementing different Machine Learning models just because I had never seen how to implement one, in addition the questions are very confusingly worded and you have no idea what the question wants you to do. Make sure to attend EVERY SINGLE OFFICE HOUR, every minute you go to the office hour is an hour you save being confused on the labs. The TAs and professor are very helpful in clarifying what the question wants and helping you with the coding aspect. Discussions are helpful but the TAs just don't have enough time to cover lecture material and help with Labs. It would have been much more beneficial if this class was broken into a lecture and a lab portion. The midterm isn't too bad as long as you do all the previous midterms and get used to his style of asking questions as he generally asks the same types of questions every year. Overall this class isn't difficult topic-wise but extremely time-consuming just because of how confusing everything is so make sure to leave enough time.
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