MSCS 612N - Deep Learning

4 Credits

This course covers artificial neural networks and their variances, especially deep neural networks, from a
biologically-inspired perspective to the current open problems. The course emphasizes both modeling
methodology (including feedforward, recurrent, convolutional, and generative adversarial neural
networks) and the practical implementation of neural networks modeling using Python and R. Students
will delve into the realm of learning from data in various formats, including images, videos, sound, and
text, to predict outcomes for unseen data or generate novel data. Students will have a semester-long
project and report their progress through distinct phases of solving their desired research questions. This
multifaceted approach fosters continuous skill enhancement through exploration, practice, and critical
thinking, empowering students to excel in the evolving field of deep learning.