intro to DEEP LEARNING (Undergrad)
CSCI-UA 480 075 · FALL 2025 · NYU COURANT INSTITUTE OF MATHEMATICAL SCIENCES
| INSTRUCTOR | Alfredo Canziani |
| LECTURES | Tue/Thu 12:00 – 13:45 |
| CODE | 2025 repo |
| BLACKBOARDS | Google Drive |
| READINGS | Google Drive |
| SLIDES | Google Drive |
This is second offering of my new course is meant to be an introduction to Deep Learning research for undergraduate (or advanced high school) students.
The aim of this course is to get the students fluent in reasoning, using:
- maths (linear algebra, calculus, logic),
- diagrams and schematics (abstract graphical language),
- graphs (function plotting and asymtotic behaviour),
- physics (reducing systems to their base parts to identify emerging collective behaviours), and
- coding (empirical verification of proposed hypothesis).
To test the students’ knowledge, the course uses 6 quizzes throught the semester, 4 homework assignments, 2 projects, and a final oral exam, where the student is examined on final project significance and originality, project presentation and defence, course content knowledge, and communication effectiveness.
Selected final projects and code written in class can be found in the GitHub repo, slides, blackboards, and suggested readings can be found on Google Drive. All links are provided at the top of this web page.
Lectures
Will be posted on YouTube and linked here.