Bachelor of Science in Business Analytics
The Bachelor of Science (Business Analytics) degree programme is an inter-disciplinary undergraduate degree programme offered by the School of Computing with participation from the Business School, Faculty of Engineering, Faculty of Science, and Faculty of Arts and Social Sciences. This is a four-year direct honours programme which offers a common two-year broad-based inter-disciplinary curriculum where all students will read courses in Mathematics, Statistics, Economics, Accounting, Marketing, Decision Science, Industrial and Systems Engineering, Computer Science and Information Systems. Students in their third and fourth years of study may choose elective courses from two lists of either functional or methodological elective courses. Functional elective courses span business functions or sectors of marketing, retailing, logistics, healthcare, etc. Methodological elective courses include those related to big data techniques, statistics, text mining, data mining, social network analysis, econometrics, forecasting, operations research, etc. In sum, these elective courses span the most exciting and challenging areas of business analytics practice in the industry today.
Students with Grade Point Average (GPA) of 4.00 or higher may opt to replace Industry Experience Requirement by BT4101 B.Sc. Dissertation. Students who aim for Honours (Highest Distinction) must pass the BT4101. Students with GPA of 4.00 or higher after completing at least 70% (i.e. 112 units) of the total unit requirement for the degree programme may opt to replace the IS4010 Industry Internship Programme by BT4101 (12 units).
Note that the BT4101 project selection process takes place one semester ahead of the semester in which the students commence BT4101. Thus the students can tentatively select BT4101 projects; but the condition “GPA of 4.00 or higher after completing at least 70% (112 units) of the total unit requirement for the degree programme” must be satisfied before they can commence BT4101 in lieu of IS4010.
Students who attended NOC Programme may:
- count ETP3202L Innovation & Enterprise Case Study and Analysis (8 units) partially in lieu of BT4101 BSc Dissertation (8 out of 12 units).
- count ETP3203L Innovation & Enterprise Internship Practicum (8 units) partially in lieu of BT4101 BSc Dissertation (4 out of 12 units). The remaining 4 units can be used to meet the total unit requirement of Programme Electives at level-3000. ETP3203L is not mapped to any specific course in IS/BZA programme.
- count ETP3206L Innovation & Enterprise Internship (12 out of 16 units) towards Industrial Experience Requirement (i.e. IS4010 Industry Internship Programme). The remaining 4 units will be counted as unrestricted electives.
Courses | Units | Sub totals |
|---|---|---|
| 40 | ||
| University Level Requirements: 6 University Pillars | 24 | |
| Digital Literacy — CS1010A Programming Methodology1 | 4 | |
| Critique and Expression — GEX% | 4 | |
| Cultures and Connections — GEC% | 4 | |
| Data Literacy — BT1101 Introduction to Business Analytics | 4 | |
| Singapore Studies — GES% | 4 | |
| Communities and Engagement — GEN% | 4 | |
| Computing Ethics | 4 | |
IS1108 Digital Ethics and Data Privacy | 4 | |
Interdisciplinary & Cross-Disciplinary Education Comprises of Interdisciplinary (ID) Courses and Cross-disciplinary (CD) Courses Students are required to take 12 units from the above courses with at least two ID courses and no more than one CD course to satisfy the 12 units required in this group. | 12 | |
PROGRAMME REQUIREMENTS Note that at least 80% of the unit requirements in a Bachelor programme’s major must be at level 1000 to 4000. | 80 | |
Core Courses | 60 | |
MA1521 Calculus for Computing | 4 | |
MA1522 Linear Algebra for Computing | 4 | |
BT2101 Econometrics Modeling for Business Analytics | 4 | |
BT2102 Data Management and Visualisation | 4 | |
CS2030 Programming Methodology II | 4 | |
| CS2040 Data Structures and Algorithms | 4 | |
IS2101 Business and Technical Communication 2 | 4 | |
ST2334 Probability and Statistics 3 | 4 | |
BT3103 Application Systems Development for Business Analytics | 4 | |
| IS3103 Information Systems Leadership and Communication | 4 | |
BT4103 Business Analytics Capstone Project | 8 | |
| BT4101 B.Sc. Dissertation or Industry Experience Requirement 4 | 12 | |
Programme Electives (PE) | 20 | |
Business Applications Analytics Methods Technology Implementation | All courses are 4 units each. | |
UNRESTRICTED ELECTIVES | 40 | |
Grand Total | 160 |
Footnotes:
1 Students can refer to: https://www.nus.edu.sg/registrar/academic-information-policies/undergraduate-students/general-education/for-students-admitted-from-AY2021-22 for the requirements for University Level Requirements. Two programme requirements are used to satisfy the new university level requirements, specifically BT1101 will satisfy the Data Literacy pillar and CS1010A/S will satisfy the Digital Literacy pillar. CS1010A will be offered only once in Semester 1 of each AY. Students will take CS1010S in place of CS1010A in semester 2.
2 Taught by the Centre for English Language Communication.
3 If a student has taken (ST2131 or MA2116 or MA2116T) and ST2132, then the student does not need to take ST2334.
4 Students may take any internship programmes that are at least 12 units and of at least 6 months continuous duration (e.g. IS4010 Industry Internship Programme, CP3880 Advanced Technology Attachment Programme, NUS Overseas Colleges) to satisfy the industry experience requirement. Students with GPA of 4.00 or higher may opt to replace the Industry Experience Requirement by BT4101 B.Sc. Dissertation. Students who aim for Honours (Highest Distinction) must pass the BT4101. Students with GPA of 4.00 or higher after completing at least 70% (i.e. 112 units) of the total unit requirement for the degree programme may opt to replace the Industry Experience Requirement by BT4101 (12 units).
Students may choose to read one or more specialisations for the BSc (Business Analytics) programme. In the case of common courses between these specialisations, the extent of double counting should be no more than 8 units among the specialisations. To ensure academic integrity of NUS specialisations, at least 60% of the Specialisation requirements to be earned from courses read at NUS. Note that at least 60% of the Unit requirements in a Bachelor programme’s specialisation must be at level 1000 to 4000.
Some of the courses require pre-requisites from outside this list. Students must have the pre-requisites to take them.
(A) Financial Analytics Specialisation
To be awarded the Financial Analytics Specialisation, students must complete 5 courses (20 units) from the prescribed list below:
- BT3102 Computational Methods for Business Applications
- BT4012 Fraud Analytics
- BT4013 Analytics for Capital Market Trading and Investment
- BT4016 Risk Analytics for Financial Services
- BT4221 Advanced Analytics with Big Data Technologies
- IS4226 Systematic Trading Strategies and Systems
- IS4228 Information Technologies in Financial Services
- IS4234 Governance, Regulation, and Compliance Technology
- IS4302 Blockchain and Distributed Ledger Technologies
- IS4303 IT-mediated Financial Solutions and Platforms
(B) Machine Learning-based Analytics Specialisation
To be awarded the Machine Learning-based Analytics Specialisation, students must complete 5 courses (20 units) from the prescribed list below:
- BT3017 Feature Engineering for Machine Learning
- BT4012 Fraud Analytics
- BT4014 Analytics Driven Design of Adaptive Systems
- BT4221 Advanced Analytics with Big Data Technologies
- BT4222 Mining Web Data for Business Insights
- BT4240 Machine Learning for Predictive Data Analytics
- BT4241 Causal Impact Analytics for Business Applications
- BT4301 Business Analytics Solutions Development and Deployment
- CS3243 Introduction to Artificial Intelligence
- CS4248 Natural Language Processing
- IS4246 Smart Systems and AI Governance
(C) Marketing Analytics Specialisation
To be awarded the Marketing Analytics Specialisation, students must complete 5 courses (20 units) from the prescribed list below:
- BT3017 Feature Engineering for Machine Learning
- BT4014 Analytics Driven Design of Adaptive Systems
- BT4015 Geospatial Analytics
- BT4211 Data-Driven Marketing
- BT4212 Search Engine Optimization and Analytics
- BT4222 Mining Web Data for Business Insights
- IS3150 Digital Media Marketing
- IS4241 Social Media Network Analysis
- IS4262 Digital Product Management
