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Finance Fundamentals in Python

Gain the introductory skills you need to make data-driven financial decisions in Python—using pandas, NumPy, statsmodels, and pyfolio libraries.
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PythonApplied Finance25 hours20,237

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Track Description

Finance Fundamentals in Python

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.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    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.

  • Course

    2

    Intermediate Python for Finance

    Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

  • Project

    bonus

    Analyze Your Stock Portfolio for Risks and Returns

    Use mean-variance optimization to find optimal portfolio weights and then check how well they would have performed.

Finance Fundamentals in Python
6 Courses
Track
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