• Course logistics & Programming basics (1/8/2026)
    Course goals and logistics. Programming basics. Introduction to Colab notebooks and Python syntax. Numerical program with NumPy.
    [Programming Basics Colab Notebook]
  • Linear Algebra I (1/15/2026)
    Vectors, linear combinations, and dot products.
    [Linear Algebra I - lecture notes] [Linear Algebra I - lecture slides]

    Suggested Material:

  • Linear Algebra II (1/29/2026)
    Matrix inverse, range, nullspace, change of basis, projection.
  • Statistics and PCA (2/12/2026)
    Mean, variance, covariance, principal components analysis, denoising, dimensionality reduction.
  • Probability (2/26/2026)
    Introduction to basic probability theory, bernoulli processes, expectation, variance, poisson processes.
  • ANOVA & Linear Regression (3/12/2026)
    Analysis of variance (ANOVA) and linear regression.