Courses
Formally, these work towards an AB in mathematics and computer science.
Courses I found especially elegant or compelling are
highlighted in blue. Graduate-level courses are
marked with an asterisk (*).
Technical
Math
- Math 25a: Theoretical Linear Algebra
- Math 25b: Real Analysis
- Math 122: Algebra I
- Math 113: Complex Analysis
- Math 118R: Dynamical Systems
- Math 114: Measure Theory and Functional Analysis
- MIT 18.338: Random Matrix Theory*
- Math 166r: Semi-Riemannian Geometry
Statistics
- Stat 110: Introduction to Probability
- Stat 111: Introduction to Statistical Inference
- Stat 185: Unsupervised Learning
- Stat 195: Statistical Learning Theory
- Stat 210: Advanced Probability I*
- Stat 212: Advanced Probability II*
CS
- CS 61: Systems Programming
- CS 124: Data Structures and Algorithms
- MIT 6.036: Introduction to Machine Learning
- CS 153: Compilers
- MIT 6.438: Graphical Models*
- CS 91R: Supervised Research*
- CS 121: Theory of Computation
- MIT 6.5940: TinyML*
Other
- Applied Math 115: Mathematical Modelling
- Physics 231: Computational Neuroscience*
- Physics 181: Statistical Mechanics
- Neuro 105: Systems Neuroscience
Nontechnical
- Ec 10a: Introduction to Microeconomics
- Ec 10b: Introduction to Macroeconomics
- Ec 1011a: Advanced Microeconomics
- Social Studies 10a: Social Theory I
- English 185E: The Essay, History and Practise
- Expos 20: Writing Seminar
- Gened 1043: African Spirituality
- Gened 1071: 20th Century Film
- Gened 1084: The First Nine Months
- Gened 1161: Theism and Morality
Teaching
- Stat 210: Advanced Probability I*
- Physics 231: Computational Neuroscience*