Course Syllabus


Course Information


Course Learning Outcomes (CLOs)

At the completion of the course, students will be able to...

  1. Identify problems addressable by data-driven solutions.
  2. Develop datasets that can be used for building machine learning-enabled technologies.
  3. Describe the relationship between descriptive/explanatory modeling in statistics and predictive modeling in machine learning.
  4. Build data models for predictive analytics using machine learning tools.
  5. Determine the mix of machine learning techniques applicable for a problem.
  6. Evaluate the performance of machine learning models and data analytic techniques.

Course Summary:

Date Details Due