• • Spring 2022: The Spring 2022 poster session was covered on the CS Department Homepage and the Johns Hopkins Hub! Check the link here
  • • Spring 2022: Our course is sponspored by Intuitive Surgical for best project awarded!
  • • Spring 2021: Our virtual course during COVID-19 pandemic is featured at JHU Malone Center! Check out here.
  • • Spring 2021: Dr. Unberath is recognized with the Professor Joel Dean Excellence in Teaching Award.
  • • Spring 2021: Our course achievement is shared on JHU Hub! Read the article here.
  • • Fall 2020: Our course is supported by a Google Cloud Education Grant.
  • • Fall 2020: We are delighted to announce that, as in previous semesters, we have partnered with Intuitive Surgical to offer Best Project Awards!
  • • Fall 2019: Our final poster session and Intuitive Surgical Best Project Award Ceremony was covered by the Malone Center for Engineering in Healthcare News Outlet. Read the article here.
  • • Fall 2019: Partnership with Intuitive Surgical has been confirmed!
  • • Fall 2019: We are happy to announce that our course is supported by a Google Cloud Education Grant.
  • • Spring 2019: Our final poster session and Intuitive Surgical Best Project Award Ceremony was covered in the Johns Hopkins Hub. Read the article here.
  • • Spring 2019: Intuitive Surgical has agreed to sponsor two Best Project Awards (USD 600 each) for the best final project in the 482 and 682 section of the course!
  • • Spring 2019: We are happy to announce that our course is supported by a Google Cloud Education Grant.


Q: Where do I find information on "xyz"?
A: Please refer to the syllabus, very likely you will find information there. If it's not in the syllabus, then please reach out to the course staff.
Q: How should I best reach out to the course staff?
A: Almost all questions should be asked on Piazza (consider using Piazza's search functionality to check whetehr a similar question has been answered before). If you deem Piazza inappropriate (e.g. for sensitive issues) you can email the instructors directly.
Q: I was not able to enroll for the class. Can I sit in?
A: Generally, if you are part of the Hopkins community (student/staff/faculty) you are welcome to sit in. If we're running out of space, we would kindly ask that you allow registered students to attend.

Course Staff

2022 Spring Staff

Mathias Unberath

2022 spring CA:

Cong Gao, Zhuoying Li, Hao Ding, Jieneng Chen, Jessica Su, Krushang Vaghasia

2021 Spring Staff

Mathias Unberath
Hao Ding

2021 spring CA:

Cong Gao, Kinjal Shah, Yicheng Hu, Cindy Huang, Jong Shin, Aidt Murali

2020 Fall Staff

Mathias Unberath
Hao Ding

2020 fall CA:

Cong Gao, Matt Figdore, Nan Huo, Shreyash Kumar, Shreya Chakraborty

2019 Fall Staff

Mathias Unberath
Jie Ying Wu
(TA, lab co-Instructor)
Alex Gain

2019 fall CA:

Cong Gao, Mingxi(Sadie) Xu, Yulai Bi, Junbin Huang, Michael Lepori

2019 Spring Staff

Mathias Unberath
Jie Ying Wu
(TA, lab co-Instructor)

2019 spring CA:

Chenglin Yang, Ben Pereira, Tom Wan, Yeping Wang, Sonakshi Grover

Webpage Manager

What students say ...

Quotes from the Spring 2022 evaluation

Quite a bit of in-depth HW that cover good topics!

The best aspect of this course was

-the bottom-up teaching approach. Rather than simply jumping into PyTorch implementations the course made sure to elaborate on the fundamental theory that makes neural networks work.

Quotes from the Spring 2021 evaluation

I really appreciate how well rounded the course was

- covering fundamentals, applications across many different fields, and the socioeconomic factors that come into play. It was definitely an important perspective to have in an introduction to the field.

Training deep learning networks takes a really long time.

So that was definitely a struggle working on the homework to have sufficient time to rerun the network with numerous different parameters.

Very comprehensive and exciting course. One of the best I've taken.

Quotes from the Fall 2020 evaluation

Great course but be prepared to commit a lot of time to the course

It is very difficult but worthwhile class.

Great course, must take if interested in AI/DL.

Excellent lectures, interesting homework problems and coverage of cutting edge topics in DL.

Start your homeworks early, training takes TIME!

Quotes from the Fall 2019 evaluation

Deep Learning is a hard class, but also one of the best classes I have taken at Hopkins!

The learning curve is enormous!

The coursework is tough but interesting. The grading, at the same time, always appeared fair to me.

It is difficult

but you will get great exposure to practical implementations of deep learning.

Quotes from the Spring 2019 evaluation

Best CS course at Hopkins by far!

The professor and the TAs are all very passionate on teaching this course. I have learnt many things from this course.

Heavy workload!

you'll learn a lot, very interesting. Good memes in lecture slides!

Time consuming!

Really clear your schedule to make sure you have the time to take this course. It is difficult and incredibly time consuming. That being said, it is also very rewarding. I would strongly recommend it..