1
Tue, Mar 28
Lecture 1:
Introduction
Thu, Mar 30
Lecture 2:
Image Classification
Fri, Mar 31
Recitation:
Python and NumPy basics
2
Tue, Apr 4
Lecture 3:
Regularization and Optimization
Thu, Apr 6
Lecture 4:
Neural Networks and Backpropagation
Fri, Apr 7
Recitation:
Backpropagation
3
Tue, Apr 11
Lecture 5:
Convolutional Neural Networks (CNNs)
Thu, Apr 13
Lecture 6:
Training Neural Networks (Part 1)
Fri, Apr 14
Recitation:
Project design
Assignment 1 due at 11:59pm
4
Tue, Apr 18
Lecture 7:
Training Neural Networks (Part 2)
Thu, Apr 20
Lecture 8:
Visualizing and Understanding
Fri, Apr 21
Recitation:
Pytorch tutorial
Mon, Apr 24
Project proposal due at 11:59pm
5
Tue, Apr 25
Lecture 9:
Self-supervised Learning
Thu, Apr 27
Lecture 10:
Self-supervised Learning Part 2
Fri, Apr 28
Recitation:
Mid-term preparation
Assignment 2 due at 11:59pm
6
Tue, May 2
Lecture 11:
Vision and Language + RNNs
Thu, May 4
Mid-term exam
Mid-term exam
Fri, May 5
Recitation:
Sequence Learning
7
Tue, May 9
Lecture 12:
Attention and Transformers
Thu, May 11
Lecture 13:
Modern Architectures
Fri, May 12
Recitation:
Midterm answer release + explaination
8
Tue, May 16
Lecture 14:
Structured Prediction (Detection + Segmentation)
Thu, May 18
Lecture 15:
Generative Models
Fri, May 19
Recitation:
Foundation Models
Project milestone due at 11:59pm
9
Tue, May 23
Lecture 16:
Reinforcement Learning
Assignment 3 due at 11:59pm
Thu, May 25
Lecture 17:
Segment Anything
Guest Lecture: Ross Girshick
Research Scientist at Facebook AI Research (FAIR)
Fri, May 26
Recitation:
NanoGPT
10
Tue, May 30
Lecture 18:
Interpretable Machine Learning
Guest Lecturer: Been Kim
Research Scientist at Google Brain
Thu, Jun 1
Lecture 19:
From LLMs to Self-Improving AI
Guest Lecturer: Jianfeng Gao
Distinguished Scientist & Vice President at Microsoft Research
Project poster submission due at 11:59pm
11
Mon, Jun 5
Final exam slot
Time: 10:30 - 12:20 PM
Location: CSE2 G01 and G10
Project poster session
Tue, Jun 6
Project final report due at 11:59pm