Deep Learning and Artificial Intelligence Methods

This course presents an application-focused and hands-on approach to learning neural networks and reinforcement learning. It can be viewed as first introduction to deep learning methods, presenting a wide range of connectionist models which represent the current state-of-the-art. It explores the most popular algorithms and architectures in a simple and intuitive style.

Course Content

• The fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning
• Feed-forward neural networks, convolutional neural networks, and the recurrent connections to a feed-forward neural network
• A brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism.