Basic Financial Mathematics , Sungkyunkwan University, Spring 2025
Financial Mathematics (graduate), Sungkyunkwan University, Spring 2024-2026
Advanced Financial Mathematics (graduate), Sungkyunkwan University, Fall 2025
AI for Financial Engineering, K-MOOC, Winter 2021
Financial Derivatives, Chonnam National University (CNU), Fall 2020
Financial Statistics, Chonnam National University (CNU), Spring 2020-2023
Basic Financial Mathematics, Chonnam National University (CNU), Spring 2020
Mathematics in Financial Society, Yonsei University, Fall 2017, Spring 2018
Computational and Applied Mathematics, Sungkyunkwan University, Fall 2024-2025
Scientific Computing and Deep Learning, Fall 2026
Probabilistic Generative Models (graduate), Sungkyunkwan University, Fall 2024
Machine Learning (graduate), Chonnam National University (CNU), Spring 2022
Deep Learning (graduate), Chonnam National University (CNU), Fall 2020-2022
Advanced Deep Learning (graduate), Chonnam National University (CNU), Fall 2023
Machine Learning, Chonnam National University (CNU), Spring 2023
Deep Learning, Chonnam National University (CNU), Fall 2021-2023
Advanced Machine Learning, Chonnam National University (CNU), Spring 2023
Advanced Deep Learning, Chonnam National University (CNU), Fall 2023
Calculus 1, Spring 2026
Calculus 2, Fall 2026
Data Science Computing (graduate), Chonnam National University (CNU), Spring 2021
Linux Systems, Chonnam National University (CNU), Fall 2021-2022
본 연구실에서 금융수학을 공부하고자 하는 학생들은 아래의 핵심 내용을 숙지해야 하며, 해당 내용은 다음 교과목들에서 체계적으로 다룹니다.
기초금융수학 (Basic Financial Mathematics)
주식·채권·선물·옵션 등 금융 시장의 기본 지식
* 경영학과의 '투자론', '파생상품론' 등 관련 교과목으로 대체 가능
전산응용수학 (Computational and Applied Mathematics) or 과학계산과 딥러닝 (Scientific Computing and Deep Learning)
머신러닝과 딥러닝의 기초
* 통계학과, 컴퓨터공학과, 전자전기공학부 개설 머신러닝 관련 교과목으로 대체 가능
금융수학 (Financial Mathematics)
파생상품의 기본지식, 확률 미적분학, 블랙–숄즈 이론
고급금융수학 (Advanced Financial Mathematics)
머튼 투자–소비 모형, PG-DPO, Deep BSDE 등 확률제어 기반 딥러닝 기법