• Linear Algebra I (1/6/2022)
    Course goals and logistics. Vectors, linear combinations, span, matrices as linear transformations, matrix multiplication, determinants, matrix inverse, range, nullspace.

    Suggested Material:

  • Programming basics (Optional) (1/13/2022)
    Programming basics. Introduction to Colab notebooks and Python syntax. NumPy.
  • Linear Algebra II (1/20/2022)
    Change of basis, eigenvalues and eigenvectors, principal components analysis (PCA).
  • Probability and Statistics I (2/3/2022)
    Introduction to basic probability theory & useful distributions (normal, binomial, poisson)
  • Probability and Statistics II (2/17/2022)
    Applied statistics. Significance testing using formal methods (e.g. T-test, ANOVA) vs. resampling techniques (bootstrapping & permutation testing). Model selection using cross validation.
  • Differential Equations (3/3/2022)
    Introduction to ODEs and methods for solving. Linear dynamical systems. Leaky integrate-and-fire model neuron.