Sustainable Development Goals
Abstract/Objectives
With the rapid development of science and technology accelerating the flow of information, multi-skills are essential skills in this rapidly changing era, and Fintech, which combines both finance and technology, is a topic worthy of discussion. This course aims to clarify the essence of FinTech, innovative technologies, and key trends, including financial data analysis, risk management and other financial-related knowledge, as well as innovative applications such as machine learning and deep learning. Relevant scholars and experts are invited to give speeches in the course to expand the breadth of the course. With program implementation and oral presentations, students can apply what they have learned.
Results/Contributions

■  The ability to discover, analyze, solve problems and to research independently. (20%)

■  The ability to integrate and innovate communication technology. (15%)

■  The ability to learn new knowledge and techniques. (50%)

■  The ability to possess team spirit and to comply with professional ethics. (15%)

This course is jointly offered by quantitative finance and electrical engineering professors. It combines both the electrical information engineering and financial related knowledge with the goal of cultivating cross-domain talents. The course is composed of financial engineering and artificial intelligence technology, including robot financial management, financial data analysis, machine learning, deep learning, etc. In the course, students are encouraged to participate in investment competitions held by Taiwan Stock Exchange, which accumulated the experience in financial market. In the course, relevant scholars and experts are invited to give speeches to increase students' understanding of blockchain, cryptocurrencies, futures, options, etc. And expand students' options for future outlets combined with motor information-related technologies.

Keywords
Financial EngineeringFinancial Data AnalysisRisk ManagementMachine LearningDeep LearningNeural Networks
Contact Information
翁詠祿
ylueng@ee.nthu.edu.tw