Program of Study — Course Requirements
(I) General Education Module (46 credits)
The General Education Module comprises General Education Core Courses and Specialized Education Courses.
1. General Education Core Courses (23 credits)
Students are required to complete 23 credits, including 15 credits of Ideological and Political Theory Courses and 8 credits chosen from the Seven General Education Elective Modules (select any four of the seven modules). For detailed requirements, refer to the curriculum for the Seven General Education Elective Modules and the program-specific study guide.
2. Specialized Education Courses (23 credits)
Students are required to complete 23 credits. For detailed requirements, refer to the respective Specialized Education curriculum and the program-specific study guide.
(II) Major-Specific Module (60 credits)
The Major-Specific Module comprises Common Disciplinary Courses and Major Foundation Courses.
1. Common Disciplinary Courses (Required, 32 credits)
Course Code | Course Title | Credits | Semester | Remarks |
100693 | Mathematical Analysis I | 6 | 1 | Required |
105308 | Mathematical Analysis II | 6 | 2 | |
105309 | Mathematical Analysis III | 4 | 3 | |
105490 | Probability Theory | 4 | 3 | |
107475 | Mathematical Statistics (Honors) | 3 | 4 | |
101828 | Computer Programming | 3 | 2 | |
103298 | Advanced Algebra I | 3 | 1 | |
103299 | Advanced Algebra II | 3 | 2 |
2. Major Foundation Courses (Required, 28 credits)
Course Code | Course Title | Credits | Semester | Remarks |
102689 | Machine Learning | 3 | 5 | Required |
105503 | Deep Learning | 2 | 6 | |
103237 | Time Series Analysis | 3 | 6 | |
103294 | Nonparametric Statistics | 2 | 6 | |
103322 | Multivariate Statistical Analysis | 3 | 6 | |
100982 | Real Analysis | 3 | 4 | |
107476 | Optimization Theory and Methods | 3 | 4 | |
100923 | Regression Analysis | 3 | 5 | |
105506 | Data Structures | 3 | 3 | |
105509 | Stochastic Processes | 3 | 5 |
(III) Personalized Development Module
Track | Module | Credits Required | Notes |
Honors Track | Advanced Major Required Courses | 5 | |
Specialization Module | 8 | Select according to specialization | |
Interdisciplinary Electives | 8 | ||
Research and Innovation Practicum | 2 | Counts toward Second Classroom credits | |
Total | 23 |
1. Honors Track
Students in the Honors Program are required to complete the Honors Track. Students who transfer to the Excellence Track or Entrepreneurship Track must withdraw from the Honors Program and will forfeit all Honors Program benefits.
(1) Advanced Required Major Courses (5 credits)
Course Code | Course Title | Credits | Semester | Remarks |
100409 | Functional Analysis | 3 | 5 | Required |
102109 | Generalized Linear Models | 2 | 7 |
(2) Specialization Module (Honors Track, 8 credits)
Course Code | Course Title | Credits | Semester | Remarks |
103275 | Introduction to Data Science | 3 | 5 | Elective |
100659 | National Economic Accounting | 3 | 6 | |
101849 | Business Statistical Modeling and Decision Making | 3 | 6 | |
103278 | Distributed Computing | 2 | 6 | |
105497 | Econometrics | 2 | 6 | |
105498 | Financial Risk Management | 3 | 6 | |
105500 | Financial Modeling | 2 | 6 | |
106273 | Functional Data Analysis: Methods, Theory, and Applications | 2 | 6 | |
106274 | Causal Inference | 2 | 6 | |
106275 | Statistical Inference for High-Dimensional Data | 2 | 6 | |
100189 | Statistical Thinking | 2 | 7 | |
101592 | Sampling Techniques | 2 | 7 | |
102039 | Quantitative Finance | 2 | 7 | |
103087 | Data Analysis and Visualization | 2 | 6 | |
105504 | Survival Analysis | 2 | 7 | |
106276 | Financial Optimization | 2 | 7 | |
107477 | Design of Experiments and Observational Studies | 2 | 5 | |
103431 | Statistical Writing | 1 | 7 | |
103300 | Complex Analysis | 2 | 3 | |
102111 | Selected Readings in Statistics | 2 | 7 |
(3) Interdisciplinary Elective Recommendations (8 credits, including 1 credit of International Coursework)
Course Code | Course Title | Credits | Semester | Remarks |
103430 | Microeconomics | 2 | 2 | Elective |
100096 | Macroeconomics | 2 | 3 | |
101271 | Principles of Management | 2 | 3 | |
101376 | Principles of Accounting | 3 | 3 | |
101619 | Political Economy | 2 | 3 | |
101110 | Corporate Finance | 3 | 3 | |
107385 | Money and Banking | 2 | 3 | |
100054 | Investments | 3 | 4 | |
105508 | Database Systems | 3 | 4 | |
100202 | Bayesian Decision Theory | 2 | 6 | |
100937 | Categorical Data Analysis | 2 | 5 | |
102336 | Big Data and Its Applications in Economics | 2 | 5 | |
100016 | Social Security Systems | 2 | 6 | |
102041 | Public Finance | 2 | 6 | |
103256 | Statistical Forecasting and Decision Making | 2 | 7 | |
105510 | Text Mining | 2 | 7 | |
107478 | Computer Vision | 2 | 7 | |
\ | International Coursework | 1 | Summer |
(4) Research and Innovation Practicum Credit Requirements (2 credits)
In accordance with the credit requirements under the categories of “Academic Presentations and Lectures” and “Innovation, Entrepreneurship, and Research” as stipulated in the Provisions on Second Classroom (Practical Education) Credit Recognition and Implementation for Undergraduates at Shanghai University of Finance and Economics, students must complete 2 credits.


