Introduction to Machine Learning for Engineers

Catalog description

This course offers a comprehensive introduction to machine learning (ML). Students will gain both theoretical knowledge and practical skills required to utilize ML techniques for building Internet-of-Things (IoT) applications. The theory covers the mathematical methods that are utilized to train and test ML models. The course curriculum is designed to focus on applying ML models to realize various signal processing, communication, and control operations. The course assignments and projects involve coding-based tasks that enable the students to design and implement their own ML models and optimize them for targeted IoT applications. The high-level overview of the topics covered in this course includes the extraction of feature vectors for signal processing, deep learning (DL) for communication, and reinforcement learning (RL) control. Prerequisite(s): A MAT 214, A MAT 220, I ECE 371 and either I ECE 233 or I ECE 332.