Learn the finance and Python fundamentals you need to make data-driven financial decisions. There’s no prior coding experience needed. In this track, you’ll learn about data types, lists, arrays, and the time value of money, before discovering how to work with time series data to evaluate index performance. Throughout the track, you’ll work with popular Python packages, including pandas, NumPy, statsmodels, and pyfolio, as you learn to import and manage financial data from different sources, including Excel files and from the web. Hands-on exercises will reinforce your new skills, as you work with real-world data, including NASDAQ stock data, AMEX, investment portfolios, and data from the S&P 100. By the end of the track, you'll be ready to navigate the world of finance using Python—having learned how to work with investment portfolios, calculate measures of risk, and calculate an optimal portfolio based on risk and return.
Overview
Syllabus
- Introduction to Python for Finance
- Build Python skills to elevate your finance career. Learn how to work with lists, arrays and data visualizations to master financial analyses.
- Intermediate Python for Finance
- Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
- Introduction to Financial Concepts in Python
- Using Python and NumPy, learn the most fundamental financial concepts.
- Manipulating Time Series Data in Python
- In this course you'll learn the basics of working with time series data.
- Importing and Managing Financial Data in Python
- In this course, you'll learn how to import and manage financial data in Python using various tools and sources.
- Introduction to Portfolio Analysis in Python
- Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
Taught by
Stefan Jansen, Dakota Wixom, Adina Howe, Charlotte Werger, and Kennedy Behrman
