CSC 322 - Data & 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 302, or instructor approval.
Course Repeatability: Course may not be repeated. Maximum Repeatable Hours: 3

Click here for the Spring 2025 Class Schedule.