A quick brush up of the most important topics:

• Anaconda installation, getting started with Jupyter notebooks
• Variables, numbers, strings and print formatting
• Objects and Data Structures
• Comparison operators & Statements
• Methods & Functions

• List comprehension
• Error handling
• String manipulations
• Basic visualizations

• Systems of linear equations
• Matrices
• Matrix transformations
• Learn the NumPy library

• Eigenvalues and eigenvectors
• Matrix decomposition
• Determinant and trace
• Singular Value decomposition

• Differentiation of Univariate Functions
• Partial Differentiation and Gradients
• Chain Rule
• Constrained Optimization and Lagrange Multipliers

• Discrete and Continuous Probabilities
• Sum Rule, Product Rule, and Bayes’ Theorem
• Means and Covariances

• Descriptive Statistics
• Inferential Statistics
• Gaussian Distribution and Descriptive Stats
• Correlation Between Variables

Use statistics and visualizations to explore a dataset of a business case