CSC 322 - Data and Machine Learning

Concepts/techniques in machine learning and multidisciplinary applications. Topics include data cleaning/transformation; data visualization; association/correlation rules; data classification and predictive modeling (such as SVMs); performance analysis and scalability; data mining with tabular, multi-dimensional and unstructured data, including text, audio, images; big-data frameworks (such as Spark, Hadoop, HIVE, Pig); and emerging themes and challenges.

Credit Hours: 3

Prerequisite Courses: (CSC 231 or ISE 211) and MAT 161, or instructor approval.
Crosslisting: No
Course Repeatability: Course may not be repeated.