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. 

 

Course Level: 

Undergraduate

Prerequisites: 

The following with a grade of at least C- in each: Mathematics 340L; Computer Science 314 or 314H or Electrical Engineering 360C; Biomedical Engineering 343 or Electrical Engineering 313; and Biomedical Engineering 335 or Electrical Engineering 351K or Mathematics 362K.