APPLIED MACHINE LEARNING

Catalog description

Completes the most valuable part of the data life-cycle with the application phase. Introduction to Machine Learning concepts and techniques (like supervised and unsupervised learning, neural networks, and transformers). Covers and applies some of the most popular novel tools, libraries, APIs, and best practices in Machine Learning. Capstone project allows for real - world application of what was learned, as a valuable asset in the student’s professional portfolio. Prerequisite s: DATA 220, DATA 270.