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 |