Practical Machine Learning for Real World Applications

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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/ CMOR 302 , STAT 310 /315/ DSCI 301→COMP 341→unlocks 8 courses

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