This course studies advanced machine learning methodologies with a focus on approaches from deep learning models. Topics discussed include: history and motivation for the development of deep learning methods, gradient descent, artificial neural networks, modern approaches to artificial neural networks, various forms of deep learning architecture, training processes and techniques in deep learning. Students will be trained to implement various deep learning models and architectures using Python and various libraries for deep learning in computer vision problems. Apart from that, students will also gain experience in designing solutions to real-world problems using various deep learning models.