Course information provided by the 2025-2026 Catalog.
Learn and apply key concepts of modeling, analysis and validation from machine learning, data mining and signal processing to analyze and extract meaning from data. Implement algorithms and perform experiments on images, text, audio and mobile sensor measurements. Gain working knowledge of supervised and unsupervised techniques including classification, regression, clustering, feature selection, and dimensionality reduction.
Prerequisites REF-FA25/Corequisites REF-FA25 CS 2800 or equivalent and basic familiarity with Matlab or Python, or permission of instructor. Corequisites: None.
Enrollment Priority REF-FA25 Enrollment limited to: Cornell Tech students.
3 Credits
GradeNoAud(Letter grades only (no audit))
Class Number & Section Details
19625CS 5785 LEC 030
Meeting Pattern
TR
Aug 25 - Dec 8, 2025
Instructors
Gan, K
To be determined. There are currently no textbooks/materials listed, or no textbooks/materials
required, for this section. Additional information may be found on the syllabus provided by your professor.
For the most current information about textbooks, including the timing and options for purchase, see the
Cornell Store.
3 Credits
GradeNoAud(Letter grades only (no audit))
Class Number & Section Details
19626CS 5785 LEC 031
Meeting Pattern
MW
Aug 25 - Dec 8, 2025
Instructors
Kuleshov, V
To be determined. There are currently no textbooks/materials listed, or no textbooks/materials
required, for this section. Additional information may be found on the syllabus provided by your professor.
For the most current information about textbooks, including the timing and options for purchase, see the
Cornell Store.
