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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.

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Introduction to Python for Finance

Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.

4 hours

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Adina Howe

Assistant Professor and Data Scientist

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