Learn Python financial libraries, gather/manipulate financial data, fetch APIs for company and economic data, analyze SEC financial statements, build risk models, and apply linear regression for stock price predictions. Ideal for finance professionals.
Overview
Syllabus
Introduction to Python
- Variables
- Numeric Data Types: Int & Float
- Sequential Types: Str & List
- Definite Loops: For loops
- If-Elif-Else Statements
- Data Types: Tuples
- Build Mortgage Calculator with Python
Advanced Python
- Creating Custom Functions
- Indefinite Loops: while loops
- Data Types, Dictionary and Set
- Slicing Data Types
- Reading txt files with Python
- Analyze data from text and csv file
Numerical Python & Pandas
- NumPy Array
- Broadcasting and U-Functions
- Introduction to Pandas
- Series, DataFrame, Panel
- Manipulate live S&P data from https://www.sectorspdr.com/sectorspdr/
Data Manipulation
- 5 ways to create a DataFrame
- Slicing and Filtering DataFrame
- Lambda
- Run If and Else scenarios
- Gather and Manipulate Data with Pandas
- Analyze business data from csv files
Data Extraction & Analysis
- Get live data from APIs
- Plot data with Matplotlib
- Merge and Concat Data
- Groupby in Pandas
- What if logic in Finance with Pandas
Taught by
Art Yudin, Brian McClain, and Dan Rodney
