This course is designed for students to understand the outline of Finance and to consider the possibility to utilize Technology in Finance. The lecturers will explain broad pictures and recent trends of the topic in each class, as shown below.
This course aims to develop ability of each student to be more successful in the real world with the consideration of Finance and Data science, and also through the opportunity for students to describe their own ideas.
✔ Applicable | How instructors' work experience benefits the course |
---|---|
The lecturers of this course are engineers of Daiwa Institute of Research Ltd. |
FinTech, Data-Science, algorithm, Artificial-Intelligence, Big-Data, Economic-Indicator
✔ Specialist skills | ✔ Intercultural skills | Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class1-Class7:Lecture
This course requires students to take an active role in their own learning. It is required to submit a summary report after each class.
Course schedule | Required learning | |
---|---|---|
Class 1 | Introduction | To grasp broad picture of utilization of technology in finance |
Class 2 | Finance and Data-Science | To grasp broad picture of Data-Science in finance |
Class 3 | Financial Products and Data Analysis | To understand basics of financial products and relevant data-analysis |
Class 4 | Finance/Economic Analysis | To review general knowledge of data and theory in finance/economic analysis |
Class 5 | Market Transaction and Market Data | To understand transactions in the market and market data |
Class 6 | Financial Services and Customer Data | To grasp broad picture of financial services for customers and data of customer services |
Class 7 | Foresight of FinTech and Data-Science | To consider the foreseeable future of FinTech and data-science |
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
None
Materials will be provided on T2SCHOLA in advance and projected in the Zoom lecture
Attendance, Summary-sheet, and Report at the end of the course will be considered
This course is for doctoral course students. Other students are required to register for Advanced Artificial Intelligence and Data Science B (XCO.T484).
This lecture is supported by Daiwa Institute of Research Ltd.