INFO 3950

INFO 3950

Course information provided by the Courses of Study 2019-2020.

This course will cover intermediate-level applications of data science, with focus on discovery, interpretation, and communication of meaningful patterns in data. Topics will include regression, classification, clustering, and forecasting, with an overview of machine learning algorithms and statistical inference.

When Offered Fall.

Prerequisites/Corequisites Prerequisite: INFO 2950  or equivalent.

Distribution Category (MQR-AS)

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • 17834INFO 3950  LEC 001

  • This course will cover intermediate-level applications of data science, with focus on discovery, interpretation, and communication of meaningful patterns in data. Topics will include regression, classification, clustering, and forecasting, with an overview of machine learning algorithms and statistical inference. Prerequisite: INFO 2950 or equivalent. A course in linear algebra such as MATH 2310 is also helpful.