EE 461P: Data Science Principles

Goals, methods, and applications of data mining. Includes data preprocessing, sampling, and visualization; algorithms for machine learning; clustering, classification, and predicting and forecasting; mining the Internet for content, link structure, and usage information; search engine design and social network analysis; and statistical methods. Three lecture hours a week for one semester. Electrical Engineering 361M and 379K (Topic: Introduction to Data Mining) may not both be counted. Prerequisite: The following coursework with a grade of at least C- in each: Computer Science 314 or 314H or Electrical Engineering 422C (or 322C); Electrical Engineering 351K or Mathematics 362K; and Mathematics 340L.

Course Level: 

Undergraduate

Prerequisites: 

The following coursework with a grade of at least C- in each: Computer Science 314 or 314H or Electrical Engineering 422C (or 322C); Electrical Engineering 351K or Mathematics 362K; and Mathematics 340L.