2025-2026 Academic Catalog

Jun 27, 2025

2025-2026 Academic Catalog

MSDA 3100 - Applied Deep Learning

This course provides a comprehensive learning experience covering deep learning’s applications in domains like image recognition, natural language processing, and sequential data analysis. It combines theoretical foundations, hands-on exercises, and real-world projects to equip students with the knowledge and skills needed to leverage deep learning techniques in data analytics. Topics include PyTorch, Convolutional Neural Networks (CNNs), Sequence Modeling, Natural Language Processing (NLP), and Generative Models like Autoencoders and Generative Adversarial Networks (GANs). By course completion, students will have proficiency in deep learning principles, practical coding skills, and the ability to apply these techniques in data analytics, preparing them to use deep learning effectively for data-driven decision-making and complex problem-solving.

Prerequisites: MSDA 3050 - Applied Machine Learning

OR MSCS 3450 - Fundamentals of Artificial Intelligence

Familiarity with linear algebra and calculus is recommended, but not mandatory.

Anticipated Terms Offered: Each term