2024 Fall

DATA C182 001 - LEC 001

Formerly COMPSCI C182

Designing, Visualizing and Understanding Deep Neural Networks

Eric Kim, Naveen Ashish

Aug 28, 2024 - Dec 13, 2024

Tu, Th

06:30 pm - 07:59 pm

Evans 10

Class #:34337

Units: 4

Instruction Mode: In-Person Instruction

Offered through Data Science Undergraduate Studies

Current Enrollment

Total Open Seats: 0

Enrolled: 234

Waitlisted: 0

Capacity: 234

Waitlist Max: 50

No Reserved Seats

Hours & Workload

1 hours of the exchange of opinions or questions on course material per week, 3 hours of instructor presentation of course materials per week, and 8 hours of outside work hours per week.

Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses." This course attempts to cover that ground.

Class Description

Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not, however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses." This course attempts to cover that ground.

Class Notes

*Students must select the 999 discussion section as part of enrollment into Data C182. Selection and assignment into the actual labs happens outside of CalCentral. Instructors will provide more information during the first lecture.

*Discussion sections will be for 1 hour on Monday afternoon/evening or Tuesday.

*Prerequisites for this course in Fall 2024 are not enforced but students are expected to have background knowledge in the following areas: MATH 53, MATH 54, COMPSCI 61B, COMPSCI 70 or STAT 134 or DATA C140, and DATA C100 or COMPSCI 189

*The enrollment capacity may expand to 200-250, but we can't confirm this until the instructional capacity for the course is confirmed. show less

Rules & Requirements

Credit Restrictions

Students will receive no credit for COMPSCI 182 after completing COMPSCI W182, or COMPSCI L182. A deficient grade in COMPSCI 182 may be removed by taking COMPSCI W182, or COMPSCI L182.