|This course may be repeated for credit.|
|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.
||Gen Ed Area Dept:
|Course Format: Laboratory Course||Grading Mode: Student Option|
||Prerequisites: COMP112 OR QAC155 OR QAC156
||Fulfills a Major Requirement for: (CADS)(DATA-MN)
||Past Enrollment Probability: 50% - 74%
|SECTION 01 Hybrid in-person only|
|Special Attributes: CQC|
|Major Readings: Wesleyan RJ Julia Bookstore
Various journal articles
|Examination and Assignments: |
|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): Kaparakis,Emmanuel I. 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|