DS 6050

Deep Learning

Course Description

A graduate-level course on deep learning fundamentals and applications with emphasis on their broad applicability to problems across a range of disciplines. Topics include regularization, optimization, convolutional networks, sequence modeling, generative learning, instance-based learning, and deep reinforcement learning. Students will complete several substantive programming assignments. A course covering statistical techniques such as regression.


  • Sodiq Adewole

     Rating

     Difficulty

     GPA

    3.88

     Sections

    2

    Last Taught

    Spring 2025

  • Sheng Li

     Rating

     Difficulty

     GPA

    3.97

     Sections

    2

    Last Taught

    Spring 2025