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, 31 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 | |
105494 | Probability Theory | 3 | 3 | |
102480 | Mathematical Statistics | 3 | 4 | |
101828 | Computer Programming | 3 | 2 | |
103298 | Advanced Algebra I | 3 | 1 | |
103299 | Advanced Algebra II | 3 | 2 |
2. Major Foundation Courses (Required, 29 credits)
Course Code | Course Title | Credits | Semester | Remarks |
105508 | Database Systems | 3 | 4 | Required |
107479 | Numerical Computation and Simulation | 3 | 4 | |
102689 | Machine Learning | 3 | 5 | |
103275 | Introduction to Data Science | 3 | 5 | |
103278 | Distributed Computing | 2 | 6 | |
107476 | Optimization Theory and Methods | 3 | 6 | |
103087 | Data Analysis and Visualization | 2 | 6 | |
105503 | Deep Learning | 2 | 6 | |
105510 | Text Mining | 2 | 7 | |
101410 | Linear Models | 3 | 5 | |
105506 | Data Structures | 3 | 3 |
(III) Personalized Development Module
The module consists of two tracks: the Excellence Track and the Entrepreneurship Track.
Track | Module | Credits Required | Notes |
Excellence Track | Specialization Module | 11 | Select according to specialization |
Interdisciplinary Electives | 9 | ||
Innovation and Entrepreneurship Practicum | 2 | Counts toward Second Classroom credits | |
Total | 22 | ||
Entrepreneurship Track | Entrepreneurship Course Cluster | 11 | Refer to the Entrepreneurship Track curriculum for details |
Entrepreneurship Practicum | 2 | Refer to the Entrepreneurship Track curriculum for details | |
Specialization Module | 5 | Select according to specialization | |
Interdisciplinary Electives | 4 | ||
Total | 22 |
1. Excellence Track
(1) Specialization Module (11 credits)
Course Code | Course Title | Credits | Semester | Remarks |
100982 | Real Analysis | 3 | 4 | Elective |
103300 | Complex Analysis | 2 | 3 | |
100659 | National Economic Accounting | 3 | 6 | |
101849 | Business Statistical Modeling and Decision Making | 3 | 6 | |
103322 | Multivariate Statistical Analysis | 3 | 6 | |
105497 | Econometrics | 2 | 6 | |
105498 | Financial Risk Management | 3 | 6 | |
105500 | Financial Modeling | 2 | 6 | |
106274 | Causal Inference | 2 | 6 | |
100490 | Financial Statistics | 2 | 7 | |
100937 | Categorical Data Analysis | 2 | 7 | |
101592 | Sampling Techniques | 2 | 7 | |
102039 | Quantitative Finance | 2 | 7 | |
103431 | Statistical Writing | 1 | 7 | |
105504 | Survival Analysis | 2 | 7 | |
105509 | Stochastic Processes | 3 | 5 | |
107480 | Artificial Intelligence and Cognitive Science | 2 | 7 | |
107478 | Computer Vision | 2 | 7 | |
103294 | Nonparametric Statistics | 2 | 6 | |
106273 | Functional Data Analysis: Methods, Theory, and Applications | 2 | 6 | |
106275 | Statistical Inference for High-Dimensional Data | 2 | 6 | |
100189 | Statistical Thinking | 2 | 7 | |
106276 | Financial Optimization | 2 | 7 | |
100202 | Bayesian Decision Theory | 2 | 6 | |
100255 | Credit Evaluation and Big Data Risk Management | 3 | 6 | |
105499 | Financial Econometrics | 3 | 6 |
(2) Interdisciplinary Elective Recommendations (9 credits, including 1 credit of International Coursework)
Course Code | Course Title | Credits | Semester | Remarks |
103430 | Microeconomics | 2 | 2 | Elective |
100096 | Macroeconomics | 2 | 3 | |
100656 | E-Commerce | 2 | 3 | |
101271 | Principles of Management | 2 | 3 | |
101314 | Financial Accounting | 3 | 3 | |
101376 | Principles of Accounting | 3 | 3 | |
101619 | Political Economy | 2 | 3 | |
101110 | Corporate Finance | 3 | 3 | |
100319 | Information Systems Analysis and Design | 4 | 4 | |
101639 | Marketing | 2 | 4 | |
107385 | Money and Banking | 2 | 4 | |
100054 | Investments | 3 | 4 | |
100481 | Introduction to Economic Law | 2 | 4 | |
102826 | Financial Management | 3 | 4 | |
101568 | Managerial Accounting | 3 | 4 | |
100830 | International Finance | 2 | 5 | |
100831 | International Trade | 2 | 5 | |
102336 | Big Data and Its Applications in Economics | 2 | 5 | |
100016 | Social Security Systems | 2 | 6 | |
102041 | Public Finance | 2 | 6 | |
101566 | Financial Institutions and Markets | 2 | 6 | |
\ | Summer International Program | 1 | \ |
(3) Innovation and Entrepreneurship 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.
2. Entrepreneurship Track
(1) The Entrepreneurship Course Cluster follows the Entrepreneurship Track curriculum.
(2) The Specialization Module course list follows the corresponding list under the Excellence Track.
(3) The Interdisciplinary Electives course list follows the corresponding list under the Excellence Track.
