CSCI1051A-W25
Deep Learning
Deep Learning
As data becomes ubiquitous and computing resources cheaper, many disciplines have turned to deep learning to solve complicated problems. While it has achieved remarkable success in a variety of "human" tasks, deep learning is often treated as a black-box. In this course, we will study deep learning from its foundations and build an intuitive understanding for why it works. Pairing lectures with labs, we will develop cutting-edge deep learning solutions to a variety of real-world problems. We will cover neural networks, convolutional networks designed for object detection, and recurrent networks used for natural language processing. We may also explore other topics including transformers, reinforcement learning, and generative adversarial networks subject to time and interest.(Not open to students who have already taken CSCI 0451.) (CSCI 0200, CSCI 0201, MATH 0200)
As data becomes ubiquitous and computing resources cheaper, many disciplines have turned to deep learning to solve complicated problems. While it has achieved remarkable success in a variety of "human" tasks, deep learning is often treated as a black-box. In this course, we will study deep learning from its foundations and build an intuitive understanding for why it works. Pairing lectures with labs, we will develop cutting-edge deep learning solutions to a variety of real-world problems. We will cover neural networks, convolutional networks designed for object detection, and recurrent networks used for natural language processing. We may also explore other topics including transformers, reinforcement learning, and generative adversarial networks subject to time and interest.(Not open to students who have already taken CSCI 0451.) (CSCI 0200, CSCI 0201, MATH 0200)
- Term:
- Winter 2025
- Location:
- 75 Shannon Street 202(75SHS 202)
- Schedule:
- 10:00am-12:00pm on Monday, Tuesday, Wednesday, Thursday at 75SHS 202 (Jan 6, 2025 to Jan 31, 2025)
2:00pm-4:00pm on Monday, Tuesday, Wednesday, Thursday at 75SHS 202 (Jan 6, 2025 to Jan 31, 2025) - Type:
- Lecture
- Course Modality:
- In-Person
- Instructors:
- Raylen Witter
- Subject:
- Computer Science
- Department:
- Computer Science
- Division:
- Natural Sciences
- Requirements Fulfilled:
- DED WTR
- Levels:
- Undergraduate
- Availability:
- View availability, prerequisites, and other requirements.
- Course Reference Number (CRN):
- 11579
- Subject Code:
- CSCI
- Course Number:
- 1051
- Section Identifier:
- A