Skill Track

Finance Fundamentals in R

Learn the finance and R fundamentals you need to make data-driven financial decisions. There’s no prior coding experience needed. In this track, you’ll learn about fundamental R concepts including vectors, matrices, lists, and functions, before discovering how to work with time series data to evaluate index performance. Throughout the track, you’ll work with popular R packages, including xts, zoo, tidyquant, PerformanceAnalytics, and PortfolioAnalytics, 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 Apple stock data, Microsoft, investment portfolios, and data from the S&P 500. By the end of the track, you'll be ready to navigate the world of finance using R—having learned how to work with investment portfolios, calculate measures of risk, and calculate an optimal portfolio based on risk and return.

  • R
  • 28 hours
  • 6 courses
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Introduction to R for Finance

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.…

4 hours
Lore Dirick

Director of Data Science Education at Flatiron School


Lore Dirick

Director of Data Science Education at Flatiron School

Jeffrey Ryan

Creator of xts and quantmod

Joshua Ulrich

Quantitative Analyst & member of R/Finance Conference committee

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