Course Schedule and Catalog
Course Schedule - Spring Semester 2025
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
ELEC 475 001 (CRN: 20719)
LEARNING FROM SENSOR DATA
Long Title: LEARNING FROM SENSOR DATA
Department: Electrical & Computer Eng.
Instructor: Azhang, Behnam
Meeting: 2:30PM - 5:00PM T (13-JAN-2025 - 25-APR-2025)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Prerequisites: ELEC 303 OR DSCI 301 OR STAT 310 OR STAT 311
Section Max Enrollment: 60
Section Enrolled: 0
Total Cross-list Max Enrollment: 60
Total Cross-list Enrolled: 0
Enrollment data as of: 14-NOV-2024 11:44AM
Final Exam: No Final Exam
Description: Basic information theoretic metrics and probabilistic machine learning tools for signals, images, and other data acquired from sensors, including graphical models, density estimation, principal components analysis, support vector machines, and source separation. Graduate/Undergraduate Equivalency: ELEC 575. Mutually Exclusive: Cannot register for ELEC 475 if student has credit for ELEC 575. Cross-list: ELEC 575. Mutually Exclusive: Cannot register for ELEC 475 if student has credit for ELEC 575.