Students who passed the course will be able:

• to understand the theory behind deep learning methods such as Convolutional Neural Networks, Autoencoders and Boltzmann Machines,
• to develop their own framework for implementing these deep learning methods,
• to have a grasp of the trends in deep learning research,
• to have a feeling of when to use or avoid deep learning methods.