This repository hosts the educational materials for NYU’s Deep Learning course, including redesigned lecture slides and Jupyter notebooks. The curriculum covers historical foundations of deep learning, backpropagation and gradient descent, parameter-sharing architectures like recurrent and convolutional networks, and latent variable energy-based models. It serves as the sequel to the previous NYU-DLSP20 release, incorporating a restructured approach to teaching fundamental deep learning concepts.