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CS92PROD
Proseminar: Machine Learning Methods for Audio and Video Analysis

QAC 239
Spring 2021
Section: 01  
This course may be repeated for credit.
Crosslisting: CIS 239
Course Cluster and Certificates: Applied Data Science Certificate

In this course, students are introduced to machine learning techniques to analyze image, audio, and video data. The course is organized in three parts, and in each part we will first introduce how these nontraditional data can be converted into appropriate (mathematical) objects suitable for computer processing, and, particularly, for the application of machine learning techniques. Students then will learn and work with a number of machine learning algorithms and deep learning methods that are effective for image and audio analysis. We will also explore major applications of these techniques such as object detection, face recognition, image classification, audio classification, speaker detection, and speech recognition.
Credit: 1 Gen Ed Area Dept: NSM QAC
Course Format: Laboratory CourseGrading Mode: Student Option
Level: UGRD Prerequisites: COMP112 OR QAC155 OR QAC156
Fulfills a Major Requirement for: (CADS)(DATA-MN)
Past Enrollment Probability: 50% - 74%

Last Updated on MAR-08-2021
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