Intro to Deep Learning and Applications

Course Information

Instructor: Seong Jae Hwang (

Instructor Office: 공학원 439b

Lecture Upload Date: Wednesday


Online TA Office Hours: Zoom links on LearnUs

We have two regular online office hours per week. Zoom links will be shared in LearnUs.

Course Description

This course introduces the fundamentals of deep learning and discusses relevant applications. This introductory course is for those with little to no background in artificial intelligence or deep learning. Thus, the course covers the very basics of varying topics including linear algebra, artificial intelligence, machine learning, computer vision, and deep learning, mostly at a high level to introduce the audience to this field. Some recent trends in deep learning will be covered in the latter part of the course.


Linear algebra is useful but not necessary

Programming languages (tentative)

Python. Coding assignments in Jupyter Notebook file (.ipynb) in an open-source IDE Jupyter Notebook or Jupyter Lab. Other IDEs are also allowed as long as you can use .ipynb.

Useful but not necessary textbooks

Deep Learning: Ian Goodfellow, Yoshua Bengio, Aaron Courvile

Each week on learnus, you will see:


Discussion Board: 

Classum for public, anonymous Q&A.

Course Policies

Grading for AIC3100.01-00 (tentative)

Grading for AIC3100.GD-00 (tentative)


Collaboration Policy and Academic Honesty

Note on Disabilities

If you have a disability for which you are or may be requesting accommodation, you are encouraged to contact your instructor ASAP.

Course Schedule

AIC 3100 - Intro to Deep Learning and Applications