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  1. Programmes
  2. Business Analytics
  3. Curriculum (Prospective Students)

Bachelor of Science in Business Analytics

Overview

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 modules 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 modules from two lists of either functional or methodological elective modules. Functional elective modules span business functions or sectors of marketing, retailing, logistics, healthcare, etc. Methodological elective modules include those related to big data techniques, statistics, text mining, data mining, social network analysis, econometrics, forecasting, operations research, etc. In sum, these elective modules span the most exciting and challenging areas of business analytics practice in the industry today.

Students with CAP 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 CAP of 4.00 or higher after completing at least 70% (i.e. 112 MCs) of the MC requirement for the degree programme may opt to replace the IS4010 Industry Internship Programme by BT4101 (12 MCs).

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 "CAP of 4.00 or higher after completing at least 70% (112 MCs) of the MC requirement for the degree programme" must be satisfied before they can commence BT4101 in lieu of IS4010.


NUS Overseas Colleges (NOC) – Business Analytics

NUS Overseas Colleges (NOC) – Business Analytics

 

Students who attended NOC programme may:

  • Count TR3201/N Entrepreneurship Practicum (8 MCs) partially in lieu BT4101 BSc Dissertation (4 out of 12 MCs) and replace one Business Analytics programme elective at level-3000 (4 MCs).
  • Count TR3202/N Start-up Internship Programme (12 MCs) towards Industrial Experience Requirement  (i.e. IS4010 Industry Internship Programme)
  • Count TR3203/N Start-up Case Study and Analysis (8 MCs) partially in lieu of BT4101 BSc Dissertation (8 out of 12 MCs). 


Summary of degree requirements for BSc (Business Analytics)

Summary of degree requirements for BSc (Business Analytics)

 

Modules

MCs

Sub totals

COMMON CURRICULUM REQUIREMENTS  1

  40
University Level Requirements: 6 University Pillars 24  
Digital Literacy --- CS1010S Programming Methodology 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) Modules and Cross-disciplinary (CD) Modules

Students are required to take 12 MCs from the above modules with at least two ID modules and no more than one CD module to satisfy the 12 MCs required in this group.

12  

PROGRAMME REQUIREMENTS

 

80

Core Modules

60

 

MA1311 Matrix Algebra, or MA2001 Linear Algebra I 2

4

 

MA1521 Calculus for Computing, or MA2002 Calculus 2

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 3

4

 

ST2334 Probability and Statistics 4

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 5 12  

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

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 Compliance and Regulation Technology
IS4246 Smart Systems and AI Governance
IS4302 Blockchain and Distributed Ledger Technologies 

All modules are 4 MCs modules.

 

UNRESTRICTED ELECTIVES

 

40

Grand Total

 

160


Notes:

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 CS1010S will satisfy the Digital Literacy pillar.
2: Students are encouraged to take these MA module 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: For students taking Second Major in Statistics, they can replace ST2334 with ST2131 to meet first major requirement. For students taking the Second Major in Mathematics, they can replace ST2334 with both ST2131 and ST2132 to meet first major requirement. The MCs for ST2132 come from UE. For students taking the minor in Mathematics, they can replace ST2334 with ST2131 and take ST2132 as an unrestrictive elective to meet first major requirement.
5: Students may take any internship programmes that are at least 12 MCs 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 CAP 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 CAP of 4.00 or higher after completing at least 70% (i.e. 112 MCs) of the MC requirement for the degree programme may opt to replace the Industry Experience Requirement by BT4101 (12 MCs).
6: Students are encouraged to take IE2110 should they wish to choose IE4210 as an elective module.


 

Business Analytics Specialisations

Business Analytics Specialisations


 

Students may choose to read one or more specialisations for the BSc(Business Analytics) programme.  In the case of common modules between these specialisations, the extent of double counting should be no more than 8 MCs among the specialisation(s). 

Some of the modules 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 MCs:

Set I
 (Select any 2 modules)*:

  • 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 modules):

  • 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 Compliance and Regulation Technology
  • IS4302 Blockchain and Distributed Ledger Technologies

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


    (B) Marketing Analytics Specialisation

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

    Set I (Select any 2 modules)*:

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

  • Set II
    (Select any 3 modules):

  • 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 Compliance and Regulation Technology
  • IS4241 Social Media Network Analysis

  • * Students can choose to do all three modules from Set I and count one of them towards Set II to fulfil the modules 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 MCs:

    Set I
     (Select any 2 modules)*: 

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

  • Set II
    (Select any 3 modules): 

  • 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 modules from Set I and count one of them towards Set II to fulfil the modules requirement for the specialisation.

     

     

     

     

     

     

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