edX
edXMachine Learning Fundamentals
486 studentsADVANCEDEnglish
Korshub's take
This MicroMasters course arms you with a diverse toolkit. You'll study supervised algorithms for prediction, unsupervised methods for pattern discovery, and the mathematical theory that grounds them. Through practical case studies—classifying images, mining document topics, modeling personality—you'll understand not just how to build ML systems, but when to deploy each technique. Expect Python and Jupyter notebooks throughout.
About this course
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.
Price
$350
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