Spring 2024
CHEM C142 001 - LEC 001
Formerly Bioengineering C142/Chemistry C142
Machine Learning, Statistical Models, and Optimization for Molecular Problems
Teresa Head-Gordon
Class #:14749
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Chemistry
Current Enrollment
Total Open Seats:
15
Enrolled: 7
Waitlisted: 0
Capacity: 22
Waitlist Max: 10
No Reserved Seats
Also offered as:
BIOENG C142
Hours & Workload
3 hours of instructor presentation of course materials per week, 9 hours of outside work hours per week, and 1 hours of the exchange of opinions or questions on course material per week.
Other classes by Teresa Head-Gordon
Course Catalog Description
An introduction to mathematical optimization, statistical models, and advances in machine learning for the physical sciences. Machine learning prerequisites are introduced including local and global optimization, various statistical and clustering models, and early meta-heuristic methods such as genetic algorithms and artificial neural networks. Building on this foundation, current machine learning techniques are covered including deep learning artificial neural networks, Convolutional neural networks, Recurrent and long short term memory (LSTM) networks, graph neural networks, decision trees.
Rules & Requirements
Credit Restrictions
Students will receive no credit for BIO ENG C142 after completing BIO ENG 142. A deficient grade in BIO ENG C142 may be removed by taking BIO ENG 142.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials