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My name is Tom Mattson. I am on the Faculty at the University of Richmond. I spent several years as a management & technical consultant before earning my PhD in International Management from the Shidler College of Business at the University of Hawai'i at Manoa. In this course, I will introduce you to supervised & unsupervised machine learning.

The pre-requisites are a positive attitude, a willingness to learn, and some intrinsic motivation. All other pre-requisite knowledge is not essential. We will use Python in this course. However, the concepts & processes are applicable to other environments.

A few of the learning objectives are as follows:

  • Produce solutions to business problems with machine learning predictive analytics.
  • Apply machine learning methods & models to support business recommendations.
  • Understand the ethical implications of machine learning models.
  • Use Python to train & test supervised & unsupervised machine learning models.
  • Understand the differences between explanatory and predictive models.