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About This Course

This course introduces investment professionals to the biases in data science pipelines and ways to mitigate them. You will see the big picture of ethical dilemmas, biases and practical issues encountered in finance-related data science projects. You will also dive into different stages in a data science project and take a closer look at the specific biases in each stage and discuss mitigation strategies. You will learn how practitioners take apart a machine learning model, identify potential biases, and take necessary measures to mitigate them.

This course is designed for those who want to understand how biases are identified and mitigated in finance-related data science projects, and is especially suited for the translator role, which is those individuals working with and communicating between both investment and data science teams.

Course modules include:

This course is part of the Data Science for Investment Professionals Certificate.

Prerequisites

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:

What You’ll Learn

Upon completion of this online course you will be able to:

Topics Covered

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