### Python: Data Types and Data Structures

A basic introduction to the Python programming language and its data types and operations.

### Python: Logical Operations and Loops

To control program flow and iterate through collections of data.

### Python: Functions and Object-Oriented Programming

These enable us to build complex algorithms in a more flexible and organized way.

### NumPy and Basic Pandas

The industry-standard scientific calculation packages for Python.

### Pandas: Resampling and DataFrame

The most popular data manipulation tool for financial data analysis.

### Rate of Return, Mean and Variance

The basic mathematical concepts for analyzing assets and portfolios in quantitative finance.

### Random Variables and Distributions

A step beyond deceptive point estimations like mean, rate of change, and variance.

### Confidence Interval and Hypothesis Testing

To determine the accuracy of our sample mean estimations.

### Simple Linear Regression

Find the linear relationship between two random variables and measure the model significance.

### Multiple Linear Regression

Explain a random variable using the power of multiple independent variables.

### Linear Algebra

A mathematic tool used in quant finance papers for quick, large-scale calculations.

### Modern Portfolio Theory

Diversify across various assets to minimize risk and maximize return.

### Market Risk

Learn how to apply the Capital Asset Pricing Model to reduce market beta.

### Fama-French Multi-factor Models

The asset pricing model that generalizes CAPM to reduce beta across multiple factors.