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Machine Learning Fundamentals

edX, Online
10 weeks
350 USD
Next course start
1 August, 2023 See details
Self-paced Online
10 weeks
350 USD
Next course start
1 August, 2023 See details
Self-paced Online
Visit this course's homepage on the provider's site to learn more or book!

Course description

Machine Learning Fundamentals

Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

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.

Upcoming start dates

1 start date available

1 August, 2023

  • Self-paced Online
  • Online
  • English

Who should attend?


  • The previous courses in the MicroMasters program: DSE200x and DSE210x
  • Undergraduate level education in:
    • Multivariate calculus
    • Linear algebra

Course delivery details

This course is offered through The University of California, San Diego, a partner institute of EdX.

8-10 hours per week


  • Verified Track -$350
  • Audit Track - Free

Certification / Credits

What you'll learn

  • Classification, regression, and conditional probability estimation
  • Generative and discriminative models
  • Linear models and extensions to nonlinearity using kernel methods
  • Ensemble methods: boosting, bagging, random forests
  • Representation learning: clustering, dimensionality reduction, autoencoders, deep nets

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141 Portland Street
02139 Cambridge Massachusetts


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