This comprehensive course delves into both foundational and advanced concepts of machine learning and deep learning. Starting with Python, numpy, and fundamental machine learning techniques, students will explore statistical learning models, linear/logistic regression, Bayes classifiers, and ensemble methods. The journey continues into the realm of deep learning, covering multi-layer neural networks, stochastic gradient descent, backpropagation, optimization techniques, and more. A little bit more advanced topics such as recurrent and convolutional neural networks, GPT will also be addressed. Practical coursework, including programming assignments and hands-on projects, will be primarily based on Python and PyTorch.

Schedule

On tuesday, 8:45 — 11:45. Course starts on October 3

Prerequisites

We invite 2+ year students with knowledge of higher mathematics and the basics of programming in any language.