UVA Deep Learning Course

MSc in Artificial Intelligence for the University of Amsterdam.

Find Out More


Deep learning is primarily a study of multi-layered neural networks, spanning over a great range of model architectures. This course is taught in the MSc program in Artificial Intelligence of the University of Amsterdam. In this course we study the theory of deep learning, namely of modern, multi-layered neural networks trained on big data. The course focuses particularly on computer vision and language modelling, which are perhaps two of the most recognizable and impressive applications of the deep learning theory. The course is taught by Assistant Professor Efstratios Gavves. The teaching assistants are Kirill Gavrilyuk, Berkay Kicanaoglu, Peter O'Connor and Tom Runia.


Lecture 1

Introduction to Deep Learning and Neural Networks

Lecture 2

Modular Learning

Lecture 3

Advanced Optimizations

Lecture 4

Convolutional Neural

Lecture 5

Understanding ConvNets
and Transfer Learning

Lecture 6

Recurrent Neural Networks

Lecture 7

Memory Networks

Lecture 8

Unsupervised Learning
(G. Patrini)

Lecture 9

Unsupervised Learning and
Generative Models (G. Patrini)

Lecture 10

Deep Generative Models
(J. Tomczak)

Lecture 11

Structured Deep Learning
for Computer Vision

Lecture 12

Language Models and
Word Embeddings

Lecture 13

Deep Reinforcement Learning

Lecture 14

Presentations of State-of-the-Art

If you are interested in older versions of the lectures, you can find them below.

UVADLC Feb 2016 UVADLC Nov 2016

Hot Questions

During the course several interesting questions pop up. Instead of having them lost during the lectures, we put here all the questions could be of interest to more people, inside and outside the University of Amsterdam. Although not all questions are going to be immediately answered because of time constraints, the goal is to have the answers online as soon as possible. If you have an interesting question for which you would like an answer, you can always email us.

Hot questions


Contact us!

If you have any questions or recommendations for the website or the course, you can always drop us a line! The knowledge should be free, so feel also free to use any of the material provided here (but please be so kind to cite us). In case you are a course instuctor and you want the solutions, please send us an email.