BSc (Hons) in Economics and Data Science
- NTU General Admission Requirements
- A pass in H2 Level Mathematics and
- A pass in H2 Level Physics/Chemistry/Biology/Computing
- A good grade in Mathematics at Higher Level and
- A good grade in Physics/Chemistry/Biology/Computer Science at Higher Level
- Major CAP of 2.0 in Mathematics and
- Major CAP of 2.0 in Physics/Chemistry/Biology
- A good grade in Mathematics at Senior High School Level and a good grade in Physics/Chemistry/Biology at Senior High School Level
More details on admission can be found here.
Curriculum (AY2021 and onwards)
Programme | Major Requirements | Interdisciplinary Collaborative Core (ICC) | Broadening Electives | Total | |||
CORE | Prescribed Electives | Final Year Project | Common Core | Foundational Core | |||
Economics (ECON) | 24 AUs | 15 AUs | 8 AUs | 17 AUs | 15 AUs | 6 AUs | 140 AUs |
Data Science (DS) | 33 AUs | 22 AUs |
1. Core Requirements (57 AUs)
Course Type | Course Code | Course Title | AU | Total AU Load |
Core (ECON) | HE1001 | Microeconomics I | 3 | 24 |
HE1002 | Macroeconomics I | 3 | ||
HE2001 | Microeconomics II | 3 | ||
HE2002 | Macroeconomics II | 3 | ||
HE2003 | Econometrics I | 3 | ||
HE3001 | Microeconomics III | 3 | ||
HE3002 | Macroeconomics III | 3 | ||
HE3003 | Econometrics II | 3 | ||
Core (DS) | MH1805 | Calculus | 4 | 33 |
SC1003 | Introduction to Computational Thinking & Programming | 3 | ||
MH2802 | Linear Algebra for Scientists | 3 | ||
MH1812 | Discrete Mathematics | 3 | ||
SC1007 | Data Structures and Algorithms | 3 | ||
MH2100 | Calculus III | 4 | ||
MH2500 | Probability and Introduction to Statistics | 4 | ||
SC2001 | Algorithm Design and Analysis | 3 | ||
SC2207 | Introduction to Database System | 3 | ||
SC3000 | Artificial Intelligence | 3 |
2. Major Prescribed Electives Requirements (37 AUs)
ECON - Students are to choose one (1) level 3000 course and three(3) level 4000 courses, of which one (1) must be from the HE4xxx list. | (15 AU) |
DS - Students are to choose 22 AUs from the list of Data Science prescribed electives. | (22 AU) |
(Please refer to the course listings PDF document for the full list of Major PEs.)
3. Final Year Project Requirements (8 AUs)
Students with cGPA of 3.90 and above are required to do HE4099 Graduation Project (GP) to be eligible for Honours (Highest Distinction) and Honours (Distinction). Refer to the Economics website for more information on GP.
*students that are not eligible to read HE4099 must read an additional TWO level-4000 modules to be counted towards the Major Prescribed Electives requirements.
4. ICC Common Cores(17 AUs)
AUs | |
CC0002 Navigating the Digital World | 2 |
CC0001 Inquiry and Communication in an Interdisciplinary World | 2 |
CC0007 Science & Technology for Humanity | 3 |
CC0006 Sustainability: Social, Economy & Environment | 3 |
CC0005 Healthy Living & Well-being | 3 |
ML0004 Career and Entrepreneurial Development for the Future World | 2 |
CC0003 Ethics & Civics in a Multi-cultural World | 2 |
5. ICC Foundational Cores (15 AUs)
AUs | |
HW0228 Scientific Communication | 2 |
SC1015 Introduction to Data Science and AI | 3 |
Professional Internship 1# | 5 |
Professional Internship 2# | 5 |
# Students are required to do two internships. One of them must be related to Economics and the other must be related to Data Science. Each internship will be 10 weeks long and worth 5 AUs.
Students must do each internship during the Special Terms in their second and third year of studies.
6. Broadening and Deepening Electives (6 AUs)
Students may fulfill the AUs from any school or through online courses like MOOCs.
A degree in Economics at NTU provides graduates with a vast array of job opportunities in both the public and private sectors. Economic majors are valued for their critical thinking and analytical skills. They also benefit from an in-depth understanding of social organisations, culture and other social phenomena.
Upon graduation, students are expecting to work as data analysts, data scientists, economists and industry analysts who are skillful in analyzing big data.