QAC 239
Fall 2019
| Section:
01
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| This course may be repeated for credit. |
| Crosslisting:
CIS 239 |
| Certificates: Applied Data Science |
| Course Cluster: Applied Data Science Certificate |
In this course, students will learn machine learning techniques to analyze text, audio, and video data. The course consists of three parts: text analysis, audio analysis and video analysis. Each part will first introduces how these non-traditional data can be converted into mathematical objects suitable for computer processing and, particularly, for the application of machine learning techniques. Then students will learn a selection of supervised and unsupervised learning algorithms that are effective for text, audio, image/video analysis. Finally, students will explore major applications of these techniques such as sentiment analysis, speech emotion recognition, face recognition, pedestrian detection, keyframe extraction. |
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| Credit: 1 |
Gen Ed Area Dept:
NSM QAC |
| Course Format: Laboratory Course | Grading Mode: Student Option |
| Level: UGRD |
Prerequisites: COMP112 OR QAC155 OR QAC156 |
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Fulfills a Requirement for: (CADS)(DATA-MN)(PSYC) |
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Past Enrollment Probability: 50% - 74% |
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