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About This Course

Aimed at investment professionals or those with investment industry knowledge, this course offers an introduction to the basic data and statistical techniques that underpin data analysis and lays an essential foundation in the techniques that are used in big data and machine learning. It introduces the topics and gives practical examples of how they are used by investment professionals, including the importance of presenting the “data story" by using appropriate visualizations and report writing.


This course is part of a data science series. It is suggested, but not required, that learners complete the courses in the recommended order below to ensure uniform foundational knowledge.

Recommended order:

  • Data and Statistics Foundation for Investment Professionals
  • Statistics for Machine Learning for Investment Professionals
  • Machine Learning for Investment Professionals
  • Natural Language Processing for Investment Professionals

What You’ll Learn

  • Explain basic statistical measures and their application to real-life data sets
  • Calculate and interpret measures of dispersion and explain deviations from a normal distribution
  • Understand the use and appropriateness of different distributions
  • Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary)
  • Explain sampling theory and draw inferences about population parameters from sample statistics
  • Formulate hypotheses on investment problems

Skills Gained

Learn how to confidently act as the “translator” between your investment management team and data scientists to communicate complex data science concepts clearly to clients.

Topics Covered

  • Fintech



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