Power BI: Understanding machine learning concepts

Learning objectives

Learning Objectives: After completing this course, the learner should be able to:

  • Identify the appropriate ML technique for a specific problem.
  • Create an appropriate model in Power BI.
  • Interpret the output of the model.
  • Think critically about the limitations of ML and a specific model and consider the relative advantages of other models.


Matt Pickard

Instructor bio

Matt Pickard, Ph.D. earned a B.S. in Computer Science, an MBA from Brigham Young University and a Ph.D. in Management Information Systems from the University of Arizona. Before moving to Illinois to be a Professor of Accounting Data and Analytics at Northern Illinois University, he worked at the University of New Mexico, where he taught accounting information systems and developed the accounting data and analytics curriculum.
He has provided data and analytics training for a variety of organizations, including the City of Santa Fe, Sandia National Labs, the Information Systems Audit and Control Association (ISACA) Albuquerque Chapter and the Illinois Society of Association Executives. His MIS Ph.D. had a heavy data mining and analytics emphasis and was the start of his love for data and analytics. He finds data fascinating and is both overwhelmed and exhilarated to be living in this information age. He and his wife, Laura, are the parents of four beautiful girls. He enjoys woodworking and nature.

National Registry of CPE Sponsors

A Becker Professional Education is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org

Becker Professional Education Sponsor I.D. Numbers NASBA: 107294, New York: 002087, New Jersey: 20CE00226700, Texas: 009580, Ohio: CPE.186, Illinois 158.002405, Pennsylvania: PX177823

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