Vector – Vector operations – Advanced Vector operations – Slicing and Dicing – Linear transformations and Matrices – Principle of Mathematical Induction – Special Matrices – Vector Spaces – Span, Linear Independence, and Bases – Orthogonal Vectors and Spaces – Linear Least Squares – Eigenvalues, Eigenvectors, and Diagonalization – Applications in Computer Science.

Introduction to Statistics and Probability – Probability and Conditioning – Conditional Probability – Baye’s rule – Random variables – Expectation and Variance – Covariance – Discrete and Continuous Distributions – Central Limit Theorem – Statistics and Parameter estimation – Confidence intervals and Hypothesis testing.