Student, who passed the course satisfactorily will be able to:

• Describe brain-like computing and differences of neurocomputers from conventional digital computers,
• Understand various aspects of neurocomputers, feed forward and recurrent neural networks, deep structures of feed forward and recurrent neural networks, deep learning algorithms for training them and reinforcement learning.
• Applying deep learning algorithms to solve realistic problems and measure their performances.