QAC 239
Fall 2020
| Section:
01
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This course may be repeated for credit. |
Crosslisting:
CIS 239 |
Course Cluster and Certificates: 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. |
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% |
SECTION 01 | Special Attributes: CQC |
Major Readings: Wesleyan RJ Julia Bookstore
Various journal articles
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Examinations and Assignments: One Presentation |
Additional Requirements and/or Comments: PLEASE NOTE: Only graded courses can satisfy the requirements for the data analysis minor and the applied data science certificate. Courses completed with a CR/U grading mode will not satisfy the requirements of the two programs.
Professor Kaparakis will be handling pre-requisite override requests during pre-registration, but is not the instructor for this course. |
Instructor(s): Neumann,Markus Yao,Jielu Times: ..T.R.. 01:00PM-02:20PM; Location: ALLB204; |
Total Enrollment Limit: 16 | | SR major: 0 | JR major: 0 |   |   |
Seats Available: 2 | GRAD: X | SR non-major: 7 | JR non-major: 7 | SO: 2 | FR: 0 |
Drop/Add Enrollment Requests | | | | | |
Total Submitted Requests: 3 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 3 |
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