Course Detail
Units:
2.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: MG EN 1050 AND MATH 2250
Description
The course introduces two computational intelligence (CI) and machine learning (ML) techniques, neural networks and genetic algorithms. Some optimization and data analysis techniques are reviewed to ensure students are prepared to follow core concepts. To be successful in this course students must be proficient in Excel and have programming experience in Python along with meeting the pre-requisite courses of MG EN 1050 and MATH 2250.