2023년도 2학기 딥러닝 (CSED538-01) 강의계획서

1. 수업정보

학수번호 CSED538 분반 01 학점 3.00
이수구분 전공선택 강좌유형 강의실 강좌 선수과목
포스테키안 핵심역량
강의시간 월, 수 / 11:00 ~ 12:15 / 정보통신연구소 중강당 [133호] 성적취득 구분 G

2. 강의교수 정보

김원화 이름 김원화 학과(전공) 인공지능대학원
이메일 주소 wonhwa@postech.ac.kr Homepage http://mip.postech.ac.kr
연구실 RIST 4동 4412호 전화 054-279-2252
Office Hours

3. 강의목표

This is an introductory course on deep learning. This course is designed for any graduate-level students with some background in Calculus, Linear Algebra and Probability. The topics include, but not limited to, machine learning, deep neural network, regularization, optimization, graph learning and generative models. The students who successfully finish this course will gain knowledge on representation learning via deep learning.

4. 강의선수/수강필수사항

Calculus, Linear Algebra, Probability

5. 성적평가

Quiz: 30%
Assignments: 15%
Final Project: 50%
Class participation: 5%

*The criteria above is subject to change.

6. 강의교재

도서명 저자명 출판사 출판년도 ISBN
Deep Learning Ian Goodfellow The MIT Press 0000

7. 참고문헌 및 자료

https://www.deeplearningbook.org/

8. 강의진도계획

Week 1. Course logistics / Introduction
Week 2. Linear Algebra
Week 3. Probability Theory
Week 4. Numerical Computation
Week 5. ML basics
Week 6. Artificial Neural Network (ANN)
Week 7. Regularization
Week 8. Optimization
Week 9. Mid-term exam week (no class)
Week 10. Recurrent Neural Network (RNN)
Week 11. Convolution Neural Network (CNN)
Week 12. Graph Neural Network (GNN)
Week 13. Transformer / Autoencoder
Week 14. Generative models
Week 15. Representation learning
Week 16. Final presentation

9. 수업운영

- The course will be taught offline, face-to-face.
- Grading will be based on 1) three quiz, 2) a few assignments (mostly reading) and 3) final project and presentation (in groups)

10. 학습법 소개 및 기타사항

11. 장애학생에 대한 학습지원 사항

- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등

- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등

- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청