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AER 850

Introduction to Machine Learning

Fundamentals of machine learning will be introduced, including supervised, unsupervised and reinforcement learning, regression and classification problems, and the common machine learning algorithms e.g., linear regression, logistic regression, support vector machines, decision trees, random forest, and deep neural networks. Students will learn how to apply different concepts on aerospace engineering problems, e.g., smart cabin management, control systems, parts inspection and/or fault detection systems.
Weekly Contact: Lab: 1 hr. Lecture: 3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1

Prerequisites

CPS 125, MTH 425, MTH 410

Co-Requisites

None

Antirequisites

None

Custom Requisites

None

Mentioned in the Following Calendar Pages

*List may not include courses that are on a common table shared between programs.