— Applied Machine Learning for Non-Majors

Prerequisites & course information

Course Description: Machine learning methods and their application. Theory, design and evaluation of supervised/unsupervised machine learning algorithms. Practical use of matching learning methods and their challenges. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Data Science majors; Pass Two restricted to undergraduates. Credit Limitation(s): No credit if student has taken ECS 171 ; not intended for Computer Science and Computer Science Engineering Majors. Grade Mode: Letter. General Education: Science & Engineering (SE). Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Enrollment Restriction(s): Pass One restricted to Data Science majors; Pass Two restricted to undergraduates. Credit Limitation(s): No credit if student has taken ECS 171 ; not intended for Computer Science and Computer Science Engineering Majors. Grade Mode: Letter. General Education: Science & Engineering (SE).