Machine Learning with Engineering Applications
Foundations and concepts of data science and machine learning with applications to engineering problems. [3-0-2]
Prerequisite:
ONE OF
MATH 152 – Linear Systems
MATH 221 – Matrix Algebra
AND ONE OF
MATH 318 – Probability with Physical Applications
MATH 302 – Introduction to Probability
STAT 302 – Introduction to Probability
STAT 321 – Stochastic Signals and Systems
ELEC 321 – Stochastic Signals and Systems
AND ONE OF
CPEN 221 – Software Construction I
CPEN 223 – Software Design for Engineers I
CPSC 259 – Data Structures and Algorithms for Electrical Engineers
4 credits