Bachelor of Science in Business Analytics

Overview

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.

NUS Overseas Colleges (NOC) - Business Analytics

Students who attended NOC Programme may:

  • count ETP3201I/L Innovation & Enterprise Internship (12 units) towards Industrial Experience Requirement (i.e. IS4010 Industry Internship Programme)
  • 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) and replace one Business Analytics programme elective at level-3000 (4 units).
Summary of degree requirements for BSc (Business Analytics)

Courses

Units

Sub totals

COMMON CURRICULUM REQUIREMENTS  1

 40
University Level Requirements: 6 University Pillars24 
Digital Literacy — CS1010A Programming Methodology14 
Critique and Expression — GEX%4 
Cultures and Connections — GEC%4 
Data Literacy —  BT1101 Introduction to Business Analytics4 
Singapore Studies — GES%4 
Communities and Engagement —  GEN%4 
Computing Ethics4 

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

 

80

Core Courses

60

 

MA1311 Matrix Algebra, or MA1522 Linear Algebra for Computing 2

4

 

MA1521 Calculus 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 Algorithms4 

IS2101 Business and Technical Communication 3

4

 

ST2334 Probability and Statistics 4

4

 

BT3103 Application Systems Development for Business Analytics

4

 
IS3103 Information Systems Leadership and Communication4 

BT4103 Business Analytics Capstone Project

8

 
BT4101 B.Sc. Dissertation or Industry Experience Requirement 512 

Programme Electives (PE)
Complete 5 Business Analytics programme elective courses with at least 3 courses at Level-4000 and at least 3 courses must be BT coded courses.

20

 

Business Applications
DBA3712 Dynamic Pricing and Revenue Management
IE3120 Manufacturing Logistics
IS3240 Digital Platform Strategy and Architecture
BT4013 Analytics for Capital Market Trading and Investment
BT4016 Risk Analytics for Financial Services
BT4211 Data-Driven Marketing
BT4212 Search Engine Optimization and Analytics
DBA4811 Analytical Tools for Consulting
IS4241 Social Media Network Analysis
IS4242 Intelligent Systems and Techniques
IS4250 IT-enabled Healthcare Solutioning
IS4262 Digital Product Management
MKT4812 Market Analytics

Analytics Methods
BT3017 Feature Engineering for Machine Learning
BT3102 Computational Methods for Business Analytics
BT3104 Optimization Methods for Business Analytics
IE2110 Operations Research I 6 or DBA3701 Introduction to Optimisation
CS3243 Introduction to Artificial Intelligence
CS3244 Machine Learning
DBA3803 Predictive Analytics in Business
BSE4711 Econometrics for Business II
BT4012 Fraud Analytics
BT4015 Geospatial Analytics
BT4221 Big Data Techniques and Technologies
BT4222 Mining Web Data for Business Insights
BT4240 Machine Learning for Predictive Data Analytics
IS4241 Social Media Network Analysis
IE4210 Operations Research II
ST3131 Regression Analysis
ST4245 Statistical Methods for Finance

Technology Implementation
IS3107 Data Engineering
IS3221 ERP Systems with Analytics Solutions
IS3261 Mobile Apps Development for Enterprise
BT4014 Analytics Driven Design of Adaptive Systems
BT4301 Business Analytics Solutions Development and Deployment
IS4226 Systematic Trading Strategies and Systems
IS4228 Information Technologies in Financial Services
IS4234 Governance, Regulation, and Compliance Technology
IS4246 Smart Systems and AI Governance
IS4302 Blockchain and Distributed Ledger Technologies 

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 Students are encouraged to take these MA course options should they wish to pursue a more rigorous treatment of the subject topics covered
3 Taught by the Centre for English Language Communication.
4 If a student has taken (ST2131 or MA2216 or MA2116) and ST2132, then the student does not need to take ST2334.
5 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).
6 Students are encouraged to take IE2110 should they wish to choose IE4210 as an elective course.

Business Analytics Specialisations

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 specialisation(s).

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 satisfy the followings at 20 units:

Set I
 (Select any 2 courses)*:

  • BT4013 Analytics for Capital Market Trading and Investment
  • BT4016 Risk Analytics for Financial Services
  • IS4228 Information Technologies in Financial Services

Set II (Select any 3 courses):

  • BT4012 Fraud Analytics
  • BT4221 Big Data Techniques and Technologies
  • BT4222 Mining Web Data for Business Insights
  • IS3107 Data Engineering
  • IS4226 Systematic Trading Strategies and Systems
  • IS4234 Governance, Regulation, and Compliance Technology
  • IS4302 Blockchain and Distributed Ledger Technologies

Students can choose to do all three courses from Set I and count one of them towards Set II to fulfil the course requirement for the specialisation.


(B) Marketing Analytics Specialisation

To be awarded the Marketing Analytics Specialisation, students must satisfy the followings at 20 units:

Set I (Select any 2 courses)*:

  • BT4211 Data-Driven Marketing
  • BT4212 Search Engine Optimization and Analytics
  • BT4222 Mining Web Data for Business Insights

Set II (Select any 3 courses):

  • BT3017 Feature Engineering for Machine Learning
  • BT4014 Analytics Driven Design of Adaptive Systems
  • BT4015 Geospatial Analytics
  • BT4221 Big Data Techniques and Technologies
  • IS3107 Data Engineering
  • IS3240 Digital Platform Strategy and Architecture
  • IS4234 Governance, Regulation, and Compliance Technology
  • IS4241 Social Media Network Analysis

* Students can choose to do all three courses from Set I and count one of them towards Set II to fulfil the course requirement for the specialisation.


(C) Machine Learning-based Analytics Specialisation
 (new)

To be awarded the Machine Learning-based Analytics Specialisation, students must satisfy the followings at 20 units:

Set I
 (Select any 2 courses)*:

  • BT3017 Feature Engineering for Machine Learning
  • BT4222 Mining Web Data for Business Insights
  • IS4242 Intelligent Systems and Techniques

Set II (Select any 3 courses):

  • BT4012 Fraud Analytics
  • BT4221 Big Data Techniques and Technologies
  • BT4240 Machine Learning for Predictive Data Analytics
  • BT4301 Business Analytics Solutions Development and Deployment
  • CS3243 Introduction to Artificial Intelligence
  • CS3244 Machine Learning
  • IS3107 Data Engineering
  • IS4246 Smart Systems and AI Governance

* Students can choose to do all three courses from Set I and count one of them towards Set II to fulfil the course requirement for the specialisation.