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Classes

University of California, Berkeley

  1. {Computer Science} 270 Combinatorial Algorithms and Data Structures, 189 Introduction to Machine Learning, 170 Efficient Algorithms and Intractable Problems, 70 Discrete Mathematics and Probability Theory, 61C Great Ideas of Computer Architecture, 61B Data Structures, 61A The Structure and Interpretation of Computer Programs.
  2. {Electrical Engineering} 127 Optimization Models in Engineering, 126 Probability and Random Processes, 120 Signals and Systems, 16b Designing Information Devices and Systems II, 16a Designing Information Devices and Systems I.
  3. {Mathematics} 110 Linear Algebra, 104 Real Analysis.
  4. {Statistics} 134 Concepts of Probability.

University of Toronto

  1. {Computer Science} 108 Introduction to Computer Programming.
  2. {Mathematics} 223 Linear Algebra I, 232 Calculus of Several Variables, 135 Calculus, 102 Introduction to Mathematical Proofs.