The following list of classes count as modeling/analysis electives for students on the Computational Neuroscience Track. Additional courses may be petitioned for approval.
Stat 108: Computing Software
Stat 111: Theoretical Inference
Stat 121: Data Science
Stat 131: Time Series
Stat 139: Linear Models
Stat 171: Stochastic Processes
Stat 220: Bayesian Data Analysis
Stat 149: Generalized Linear Models
ENG-SCI 115/APM: Mathematical Modeling
ENG-SCI/APM 121: Intro to Optimization
ENG-SCI 155: Biological Signal Processing
ENG-SCI/APM 158: Feedback Control of Dynamical Systems
MCB 111: Mathematics in Biology
MCB 112: Biological Data Analysis
MCB 198: Advanced Math Techniques for Modern Biology
APM 50: Intro to Applied Mathematics
APM 104: Series Expansions and Complex Analysis
APM 105: Ordinary and Partial Differential Equations
APM 107: Graph Theory and Combinatorics
APM 108: Nonlinear Dynamical Systems
APM 111: Intro Scientific Computing
APM 120: Applied Linear Algebra and Big Data
CS 108: Intelligent Systems: Design and Ethical Challenges
CS 109: Intro to Data Science
CS 121: Intro to Theory of Computation
CS 124: Data Structures and Algorithms
CS 125: Algorithms and Complexity
CS 143: Computer Networks
CS 181: Machine Learning
CS 182: Artificial Intelligence