Fall 2018 Curriculum:
Deep Learning Demystified

From Linear Regression to Image Recognition

Motivation

Recent developments in deep learning have made once again made AI the "next big thing" in the tech community. Unfortunately, deep learning is also one area of AI that is perhaps among the most misunderstood by the media and general public alike. We feel that it is important to demystify deep learning as much as possible so that more people are educated about what it can and can't do, and how it can be used for good.

For members: We plan to guide a cohort of members through our deep learning curriculum, complete with in-person workshops, during the each semester of the 2018-2019 academic year. Members will then have a chance to implement this content by working on a variety of team projects in the spring.

For anyone: You can access our deep learning lessons via the links below, or via our student blog. After each in-person workshop, you will be able to find the relevant code online via our github account. We hope that these materials will serve as helpful resources for anyone wanting to learn more about deep learning and artificial intelligence.

(Note that deep learning/machine learning is only one part of the much larger field of artificial intelligence. If you are interested, we recommend you look into other topics in AI as well!)


Curriculum Outline

  1. Introduction to AI/Machine Learning
  2. Linear Regression
  3. Logistic Regression and Classification
  4. Neural Networks, Part 1 (Architecture)
  5. Neural Networks, Part 2 (Training)
  6. Neural Networks, In Practice
  7. Convolutional Neural Networks
  8. Recurrent Neural Networks
  9. Generative Adversarial Networks
  10. Next Steps

If you have any questions about our curriculum, feel free to send us a message at caisplus@usc.edu and we will do our best to get back to you promptly.