This is a comprehensive list of every single class I’ve taken at UW-Madison. I intend for this post to give people an insight into how I balanced coursework with part-time work and extracurriculars as an undergraduate student. Each semester has a star rating assigned to it which corresponds with how difficult the semester was — more stars imply greater difficulty.
I’ve denoted part-time work or internships I held during the semester as 💼 and research related projects as 🔬. I’ve also noted courses that I particularly enjoyed as (^), courses that were particularly time consuming as (!), and courses that I largely disliked as (.).
fall ‘24
- CS 704: Principles of Programming Languages
- CS 839: Systems Verification
- CS 537: Introduction to Operating Systems
- CS 542: Introduction to Software Security
- ECON 521: Game Theory and Economic Analysis
- (💼) Software Engineer Intern @ Morgridge Institute of Research
- (🔬) Research project: Developing software to visualize agricultural data.
spring ‘24 (*)
- CS 536: Introduction to Compilers (^)
- CS 639: Parallel & Throughput-Optimized Programming (.)
- MATH 728: Integer Optimization
- ECON 301: Intermediate Economic Theory
- ASIAN 357: Japanese Ghost Stories
- MUSIC 113: Music in Performance
- (💼) System Administrator Intern @ Morgridge Institute of Research
- (💼) TA @ CS 538: Theory and Design of Programming Languages
fall ‘23 (****)
- CS 538: Introduction to Theory and Design of Programming Languages
- MATH 525: Introduction to Linear Optimization (!)
- MATH 632: Introduction to Stochastic Processes (!^)
- ECON 111: Principles of Economics (!)
- HISTORY 143: History of Race and Inequality in Urban America
- MUSIC 113: Music in Performance
- (💼) System Administrator Intern @ Morgridge Institute of Research
spring ‘23 (***)
- CS 354: Machine Organization and Programming
- CS 540: Introduction to Artificial Intelligence (.)
- CS 577: Introduction to Algorithms
- MATH 431: Introduction to the Theory of Probability
- MATH 521: Analysis I (!)
- (🔬) Research project: Training and optimizing image generation models.
fall ‘22 (*)
- CS 252: Introduction to Computer Engineering
- MATH 475: Introduction to Combinatorics (^)
- ECE 537: Communication Networks (^)
- PHYSICS 201: General Physics
- MSE 299: Independent Study — Machine Learning for Engineering Research. Basic ML workflow like cleaning data, training models, and optimization.
pre-college
- CS 300: Programming II (SU ‘20)
- CS 400: Programming III (FA ‘20)
- ECE 203: Signals, Information, and Computation (SU ‘21)
- MATH 20804232: Calculus & Analytic Geometry 2 (SU ‘21) Madison College
- MATH 234: Calculus - Functions of Several Variables (FA ‘21)
- MATH 341: Linear Algebra (SP ‘22)