everything.study
COMP 341

PRACTICAL MACHINE LEARNING FOR REAL WORLD APPLICATIONS

Credit Hours: 3 · Undergraduate Upper-Level

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

Prerequisites & course information

Short Title: PRACTICAL MACHINE LEARNING Department: Computer Science Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): COMP 182 and ( MATH 102 or MATH 106 )

Sources