There is increasing public and corporate concern about bias and other unintended harmful effects resulting from data science models. This course, for both data science practitioners and managers, provides guidance and practical tools to build better models and avoid these problems. The course offers a framework to follow in implementing data science projects, and an audit process to follow in reviewing them. Case studies along with R and Python code are provided.
Mr. Grant Fleming
Grant Fleming is a Data Scientist at Elder Research, Inc., where he works on developing new data science capabilities for private and public sector organizations. He has given talks on the application of interpretability methods to machine learning algorithms, and is a co-author (with Peter Bruce) of "The Ethical Practice of Data Science," forthcoming from Wiley in 2020. Prior to working at Elder Research, Grant worked as a research contractor for USAID.