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MFIT 5008: Decision Analytics in FinTech
Course Prerequisite(s):
Course Exclusion(s): Not applicable
Course Add/drop deadline: Feb 6
(Any late add/drop will not be considered, add/drop deadline by Feb 6)
2. COURSE DESCRIPTION
This course aims to introduce decision analytics instruments and their applications in FinTech. Main topics covered in this
course include basic probability and statistics, predictive analytics, prescriptive analytics such as linear programming, integer
programming, dynamic programming and sequential decision making, stochastic models, quality control, Monte Carlo
simulation, game theory, and their applications in various areas of FinTech.
3. COURSE OBJECTIVES
The objective of this course is to teach students various important decision analytics tools such that they are equipped with this
important toolkit in FinTech.
4. COURSE LEARNING OUTCOMES
Course Learning Outcomes
CLO1. Apply predictive analytics to modeling and analysis
CLO2. Apply prescriptive analytics to modeling and analysis
CLO3. Understand the applications of decision analytics to various FinTech-related problems
5. COURSE TEACHING AND LEARNING ACTIVITIES
Course Teaching and Learning Activities
Expected
contact hours
Study Load
(% of study)
Lectures
Learning activities
Projects
39
10
10
66%
17%
17%
Total 100%
Assessment Methods
(Homework assignment, Exam,
Quiz, Class participation etc)
Brief Description (Optional) Weight (%) Aligned Course Learning
Outcomes
(CLO no in section 4)