This course provides a hands on approach to machine learning and statistical pattern recognition. The course describes fundamental algorithms for linear regression, classification, model selection, support vector machines, neural networks, dimensionality reduction and clustering. The course includes computer exercises on real and synthetic data using current software tools. A number of applications are demonstrated on audio and image processing, text classification, and more. Students should have competency in computer programming. | Prerequisite for Brooklyn Students: CS-UY 1134 AND (MA-UY 2034, MA-UY 2034G, MA-UY 3044 or MA-UY 3054) AND (MA-UY 2224, MA-UY 2222, MA-UY 2233, ECE-UY 2233, MA-UY 3012, MA-UY 3014, or MA-UY 3514) | Prerequisite for Abu Dhabi Students: (ENGR-UH 3510 or CS-UH 1050) (C- or better) AND (MATH-UH 1022 or MATH-UH 1023) AND (MATH-UH 2011Q or ENGR-UH 2010Q) | Prerequisite for Shanghai Students: CSCI-SHU 210 (C- or better) AND (MATH-SHU 140 or MATH-SHU 141) AND MATH-SHU 235
Computer Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2025)
CS-UY 4563-000 (16680)01/21/2025 – 05/06/2025 Tue,Thu11:00 AM – 12:00 AM (Morning)at Brooklyn CampusInstructed by Sellie, Linda
CS-UY 4563-000 (16681)01/21/2025 – 05/06/2025 Tue,Thu2:00 PM – 3:00 PM (Early afternoon)at Brooklyn CampusInstructed by Sellie, Linda