Machine Learning for Finance
The financial sector is experiencing a profound transformation, driven by unprecedented technological advancements. At the forefront of this revolution is machine learning, a powerful subset of artificial intelligence. This cutting-edge course is meticulously designed to equip students with the essential knowledge and skills needed to harness the full potential of AI and data science in the realm of finance. By seamlessly bridging the gap between time-honored financial theories and state-of-the-art machine learning techniques, this course offers a unique and comprehensive learning experience. Students will embark on an exciting journey, exploring the myriad ways in which sophisticated machine learning algorithms can be applied to various facets of finance.
Lecturer
Date
10th October ~ 26th December, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Thursday | 08:50 - 12:15 | A3-4-312 | ZOOM 02 | 518 868 7656 | BIMSA |
Prerequisite
Finance, Economics, Computer Science, Statistics
Audience
Undergraduate
, Advanced Undergraduate
Video Public
No
Notes Public
No
Language
Chinese
Lecturer Intro
Dr. Zhen Li is an assistant professor at BIMSA. He is also a visiting research fellow at the Chongyang Institute for Financial Studies, Renmin University of China, and the International Monetary Institute, Renmin University of China. He was a postdoctoral fellow from 2020-2022 at the School of Data Science, Fudan University, and an assistant research fellow from 2013-2016 at the Chongyang Institute for Financial Studies, Renmin University of China. Dr. Li received his Ph.D. in Finance, M.A. in Statistics, and B.A. in Finance from the Renmin University of China, and his B.E. in Software Engineering from Nanjing University. He was a visiting scholar from 2019-2020 at the School of Business, George Washington University. His current research focuses on financial machine learning, digital finance, data factors and risk management. Dr. Li has published more than 40 articles in some academic journals, such as Journal of Financial Research, Statistical Research, China Economic Review , etc.