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Machine Learning Fundamentals


In this course, part of the Data Science MicroMasters® program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.


  1. The previous courses in the MicroMasters program: 
  2. Undergraduate level education in:
    • Multivariate calculus
    • Linear algebra 

Course Format

  • Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.

Learn more and enroll on edX.