Course Schedule and Catalog
Course Schedule - Fall 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.
COMP 341 001 (CRN: 12731)
PRACTICAL MACHINE LEARNING
Long Title: PRACTICAL MACHINE LEARNING FOR REAL WORLD APPLICATIONS
Department: Computer Science
Instructor: Yao, Vicky
Meeting: 4:00PM - 5:15PM TR (25-AUG-2025 - 5-DEC-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: COMP 182 AND (MATH 102 OR MATH 106)
Section Max Enrollment: 75
Section Enrolled: 75
Waitlisted: 6 (Max 99)
Current members of the waitlist have priority for available seats.
Enrollment data as of: 19-APR-2025 11:01PM
Final Exam: Take-Home Exam
Description: This course teaches practical skills for using machine learning models. Students will
learn how to apply ML algorithms to real world problems from data collection to the final
step of reporting findings. Topics covered include: data augmentation, bias detection,
feature engineering, efficient tuning and training, model interpretation, and data
storytelling. Recommended Prerequisite(s): MATH 355/354/CAAM 335/CMOR 302, STAT 310/315/DSCI 301