Vector and matrix arithmetics (1/6/2022)

Defining and using vectors and matrices. Dot products between vectors and matrix multiplications.

**
**

Programming basics (Optional) (1/13/2022)

Python programming skills needed for this course, Computational Core, and Cognitive Core.

**
**

Linear algebra (1/20/2022)

Basic concepts in linear algebra: matrix multiplication, building up to applied topics such as Principal Components Analysis (PCA) and convolutions.

**
**

Probabilistic thinking (2/3/2022)

Probability distributions and where they come about in analyzing data. Concepts in marginal and conditional probability. Common probability distributions, such as Gaussian, Bernoulli, Poisson, etc. Bayesian probability.

**
**

Calculus (2/17/2022)

Calculus topics building up to differential equations, dynamical systems analysis and gradients.

**
**

Statistics (3/3/2022)

Fundamental concepts such as variance, standard error, and significance. Parametric hypothesis testing methods, such as t-tests and ANOVA. Bootstrapping. Cross validation.

**
**