Course Schedule and Catalog
Course Catalog - 2022-2023
COMP 341 - PRACTICAL MACHINE LEARNING
Long Title: PRACTICAL MACHINE LEARNING FOR REAL WORLD APPLICATIONS
Department: Computer Science
Grade Mode: Standard Letter
Language of Instruction: Taught in English
Course Type: Lecture
Credit Hours: 3
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Prerequisite(s): COMP 182 AND (MATH 102 OR MATH 106)
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, STAT 310/315/DSCI 301