Deep Learning Advanced Learning Path - MAI4CAREU Master in AI

This Deep Learning (DL) learning path offers a structured curriculum that delves into Deep Learning, a subfield that has been associated with the revolution of AI in the last decade, with advancements in vision, natural language processing, attention and artificial general intelligence. The impact of DL extends in societal, technological, industrial, and financial sectors – and is poised to shape our future even more profoundly.

It is based on the elective advanced course offered at the Master in Artificial Intelligence of the University of Cyprus, which was developed with co-funding from the MAI4CAREU European project. The course offers a guided exploration of DL’s fundamental principles and diverse applications, and consists of twelve units organized in three parts as shown below, which are further arranged into Introductory (eight units), and Advanced (four units) according to their level of difficulty. The recommended order for studying all materials is the one shown below (from 1 to 12).

Part I: Introduction

1. Introduction to Deep Learning
2. Deep Learning Fundamentals
3. Mathematics of Deep Learning

Part II: Deep Neural Networks

1. Principles of Deep Neural Networks
2. Convolutional Neural Networks
3. Transfer Learning and Residual Networks
4. Optimizing Deep Neural Networks
5. Recurrent Deep Neural Networks

Part III: Advanced and Emerging Topics in Deep Learning

1. Attention and Transformers
2. Generative Adversarial Networks
3. Deep Reinforcement Learning
4. Emerging Topics in Deep Learning