CS 433 - Big Data Analytics

3 Credit(s) | Lecture |
Course can be counted for credit once

Description:
This course introduces methods and platforms for analyzing large amounts of data. Classical paradigms of parallel computing - such as multireading, message passing, and accelerator programming - are presented. Machine learning and data mining techniques - such as regression, clustering, classification, and deep learning - are discussed. Platforms of computing with big data - such as graph database, distributed file systems, and map-reduce - are introduced. This course prepares students to perform predictive modeling and explore large, complex datasets.

Enrollment Requirements:
Prerequisites: CS 310 and MATH 260 and MATH 345 or permission of instructor

040860:1