Spring 2025 Applied Analytics PS5910 section 001

APPLIED DEEP LEARNING AND AI

TOPIC: APPLD DEEP LEARN A

Call Number 17304
Day & Time
Location
T 8:10am-10:00am
333 Uris Hall
Points 3
Grading Mode Standard
Approvals Required None
Instructor Siddhartha Dalal
Type LECTURE
Method of Instruction In-Person
Course Description

Deep Learning has become a cornerstone of Artificial Intelligence (AI), with applications in finance, healthcare, sports, autonomous vehicles, chatbots, national security, and artistic creations using elements of Natural Language Processing, Computer Vision, and Speech Recognition. Students will gain a solid foundation in Deep learning and its applications, starting with a compressed review of some Statistical Learning models followed by much deeper dive into Deep Neural Networks. Topics covered include Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures and Generative Adversarial Networks (GAN). Students will also learn training of agents to make optimal decisions in complex environments using Reinforcement Learning. Practical applications will demonstrate how to prepare, train, test, and validate these models.

Web Site Vergil
Department Applied Analytics
Enrollment 1 student (50 max) as of 4:06PM Friday, April 4, 2025
Subject Applied Analytics
Number PS5910
Section 001
Division School of Professional Studies
Open To Professional Studies
Note ON-CAMPUS. APAN ONLY. PRE-REQS: NEEDS ADVISOR APPROVAL
Section key 20251APAN5910K001