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.

At a Glance:
Institution: UCSanDiegoX
Subject: Data Analysis & Statistics
Level: Advanced
Prerequisites:
The previous courses in the MicroMasters program: DSE200x and DSE210x
Undergraduate level education in:
Multivariate calculus
Linear algebra
Language: English
Video Transcript: English
Associated programs:
MicroMasters® Program in Data Science
Associated skills:Jupyter, Data Science, Python (Programming Language), Forecasting, Machine Learning, Algorithms, Unsupervised Learning, Predictive Modeling