Master of Technology in Enterprise Business Analytics

Summary

The NUS Master of Technology in Enterprise Business Analytics programme (MTech EBAC) is specifically designed to meet the industry demand for data scientists who can help organisations achieve improved business outcomes through data insights. It is best suited for professionals seeking to focus on the following - methodical data exploration and visualisation, diagnostic analytics, predictive modelling using statistical and machine learning techniques, text analytics, recommender systems, and big data engineering, etc.

This stackable programme prepares you for specialist, expert and leadership roles in enterprise business analytics to create business value through strategic use of data, analytics, models and frontline tools.

Next Intake: July 2019 (Full Time) / Jan 2019 (Part Time)
Duration: Full-time 1 year (2 semesters)

Part-time 2 years (4 semesters)
Application Deadline:

    28 February 2019 
    (for full-time studies)
    15 October 2018
    (for part-time studies)

     

Fees

Full-time

Singaporeans & Singapore Permanent Residents
(aged 21 years and above)
Semester 1 S$8,375.96 + S$5,350.00 + S$2,833.60 or S$3,391.90
Semester 2 S$4,258.60 or S$3,391.90
$250.95  - Miscellaneous Fee per Semester
Total Fee (range) S$19,951.22 to S$21,376.46

Singaporeans, Singapore Permanent Residents (without subsidies) & International Students
Please contact us for fee enquiries.
isspostgrad@nus.edu.sg

Part-time

Singaporeans & Singapore Permanent Residents
(aged 21 years and above)
Semester 1 S$3,700.06
Semester 2 S$4,675.90
Semester 3 S$2,833.36 or S$3,391.90
+ S$5,350.00
Semester 4 S$4,258.60 or S$3,391.90
$132.90  - Miscellaneous Fee per Semester
Total Fee (range) S$19,951.22 to S$21,376.46

Singaporeans, Singapore Permanent Residents (without subsidies) & International Students
Please contact us for fee enquiries.
isspostgrad@nus.edu.sg

Programme Details

  • Overview
  • Modules
  • Capstone Project & Internships
  • Timetable & Exams
  • Fees
  • Admission & Application
  • Career Pathways

The MTech EBAC programme prepares students for specialist, expert and leadership roles in enterprise business analytics to create business value through strategic use of data, analytics, models and frontline tools.

By contributing to more effective utilisation and management of data analytics, you can help your enterprise to focus on big decisions so that they gain better predictive ability that can translate to higher profits. Helping enterprises to build better and more effective models will lead to improved outcomes such as more attractive pricing, higher levels of customer care, better market segmentation and highly-efficient inventory management and finally profit maximization.

Graduates of the programme will be capable of undertaking tasks such as:

  • Discovering insights from data
  • Applying concepts and techniques to solve major business problems
  • Designing and customizing marketing campaigns through efficient targeting
  • Analysing sales channels
  • Optimising the marketing mix of their organisations
  • Improving decision-making to increase returns on investments for their organisations
  • Predicting the future profitability of their organisations

 

Learning outcomes:

  • Help enterprises move towards a stronger emphasis on computer tools and statistical and machine learning techniques to develop high-performance analytics capability
  • Translate massive and complex unstructured data (e.g.: text) into insights
  • Produce predictive models to solve a broad range of problems across various business functions and units
  • Contribute to the development of more effective business strategies and plans for sustainable growth and competitive advantage

Recognition:

  • Top student is awarded the IBM Medal and Book Prize
  • Best Project Prize

MTech EBAC candidates must successfully complete the following course components to be awarded the degree:

  • Fundamental - Complete two Mandatory Topics
  • Specialist - Complete any two of four Topics

Fundamental Analytics Areas

Analytics Project Management and Delivery

Students will be equipped with practice-oriented data analytics skills and knowledge in managing analytics project. Participants will be equipped with essential skillsets to understand analytics processes and best practices, to manage data and resources, to uphold data governance, to understand structure of analytics solution, to perform data visualisation, to present insights via compelling data storytelling, and to ensure successful implementation of analytics project.

Courses:
  • Data Analytics Process and Best Practices
  • Data Story Telling
  • Data Governance & Protection
  • Managing Business Analytics Projects

Core Analytics Techniques

Students will learn the foundation skills to understand, design and solve analytics problems in the industry involving structured and unstructured data. It is a course which prepares the participants to embark upon the journey to become a data scientist in due course.

Courses:
  • (Data Analytics Process and Best Practices)
  • Statistics Boot Camp
  • Predictive Analytics – Insights of Trends and Irregularities
  • Text Analytics
  • Recommender Systems

 

Specialist Analytics Areas

Customer Analytics

Students will be equipped with the skills to manage the customer data and build analytics solutions for customer relationship management. The course will enable them to apply techniques for targeted customer marketing, to reduce churn, increase customer satisfaction and loyalty and increase profitability.

Courses:
  • Customer Analytics
  • Advanced Customer Analytics
  • Campaign Analytics

Big Data Processing

Students will learn various aspects of data engineering while building resilient distributed datasets. Participants will learn to apply key practices, identify multiple data sources appraised against their business value, design the right storage, and implement proper access model(s). Finally, participants will build a scalable data pipeline solution composed of pluggable component architecture, based on the combination of requirements in a vendor/technology agnostic manner. Participants will familiarize themselves on working with Spark platform along with additional focus on query and streaming libraries.

Courses:
  • Feature Engineering & Analytics using IOT Data
  • Graph & Web Mining
  • Big Data Engineering

Practical Language Processing

Students will be taught advanced skills in practical language processing. This includes fundamental text processing, text analytics, deep learning techniques and their application in sentiment mining and chatbots development.

Courses:
  • Text Analytics
  • New Media and Sentiment Mining
  • Text Processing using Machine Learning
  • Conversational Interfaces

Advanced Predictive Modelling Techniques

Students will be taught the advanced concepts of predictive modeling and Time Series Forecasting and their application in few special areas like Health Care & Service Industry in addition to other domains like Public Services, IT Services, Finance, Airlines, Logistics, Transport, Hotel & Tourism Industries. The topics include GLM, ARIMA & SARIMA, Transfer Functions, Survival Analysis, Image Analysis for Health Care, Management of Health & Medical Data, Service Quality Frame Work, Service Process Improvement Techniques etc.

Courses:
  • Service Analytics
  • Generalized Predictive Modeling & Forecasting
  • Health Analytics

 

A central element of the MTech programme is the project module. 

Student projects for MTech EBAC students will include intense full time engagement of 3 months with companies for full time students. For part-time students the internship engagement will be for 6-12 months. Students are allowed to conduct their project as a team-based internship if desired. The expected commitment for the project is 30 man-days per team member.

Objectives

  • Practise new technical skills in a real industry environment
  • Apply tools, methods and techniques learnt

Learning outcomes:

  • Apply business analytics methods and techniques to solve identified business problems
  • Plan and execute business analytics projects by understanding business problems, identifying appropriate analytics techniques, and then applying data exploration, model building, testing and validating of results

Read more on Internship & Placements

Timetable & Exams for Full-time Students

Year Curriculum Assessment

Year 1

Semester 1
(Jul-Nov)

BA5001 : Management of Business Analytics Project (compulsory)

  • Data Analytics Process and Best Practice
  • Data Storytelling
  • Data Governance & Protection
  • Managing Business Analytics Projects

BA5002 : Business Analytics Practice (compulsory)

  • Statistics Boot-camp
  • Predictive Analytics - Insights of Trends and Irregularities
  • Text Analytics
  • Recommender Systems

 

- Continuous assessments
- Open book written exams

Choose ONE

BA5003 : Customer Analytics

  • Customer Analytics
  • Advanced Customer Analytics
  • Campaign Analytics

BA5006 : Big Data Engineering and Web Analytics

  • Feature Engineering & Analytics with IOT Data
  • Graph & Web Mining
  • Big Data Engineering for Analytics

Year 1
(Nov-May)

Team-based Internship or Off-site Project (Nov – May)
Hands-on project with external organisation

 

- Project, presentation & report (100%)

Year 1

Semester 2
(Jan-May)

Choose ONE

- Continuous assessments (30 – 50%)
- Open book written exams (50 – 70%)

BA5005 : Specialized Predictive Modeling and Forecasting

  • Service Analytics
  • Generalized Predictive Modeling & Forecasting
  • Health Analytics

BA5004 Practical Language Processing

  • New Media and Sentiment Mining
  • Text Processing Using Machine Learning

Timetable & Exams for Part-time Students

Year Curriculum Assessment

Year 1

Semester 1
(Jan-May)

BA5001 : Management of Business Analytics Project (compulsory)

  • Data Analytics Process and Best Practice
  • Data Storytelling
  • Data Governance & Protection
  • Managing Business Analytics Projects     

 

- Continuous assessments
- Open book written exams

Year 1

Semester 2
(Jun-Nov)

BA5002 : Business Analytics Practice (compulsory)

  • Statistics Boot-camp
  • Predictive Analytics - Insights of Trends and Irregularities
  • Text Analytics
  • Recommender Systems 

- Continuous assessments (30 – 50%)
- Open book written exams (50 – 70%)

Year 2

Semester 1
(Jan-May)

Choose ONE

- Continuous assessments (30 – 50%)
- Open book written exams (50 – 70%)

BA5003 : Customer Analytics

  • Customer Analytics
  • Advanced Customer Analytics
  • Campaign Analytics

BA5006 : Big Data Engineering and Web Analytics

  • Feature Engineering & Analytics with IOT Data
  • Graph & Web Mining
  • Big Data Engineering for Analytics

 

Year 2

Semester 2
(Jun-Nov)

Choose ONE

- Continuous assessments (30 – 50%)
- Open book written exams (50 – 70%)

BA5005 : Specialized Predictive Modeling and Forecasting

  • Service Analytics
  • Generalized Predictive Modeling & Forecasting
  • Health Analytics

BA5004 Practical Language Processing

  • New Media and Sentiment Mining
  • Text Processing Using Machine Learning

 

Year 2

Team-based Internship or Off-site Project
Hands-on project with external organisation

*tbc

 

- Project, presentation & report (100%)


Students are evaluated through a combination of course work, project work and examinations. All students are required to complete a three-hour examination for each fundamental and specialist module taken.

Students who fail a module will be asked to withdraw. A minimum average grade across all examinations and practice assessments must be achieved to be awarded the degree.

The fees above are for the Academic Year 2019 / 2020.

Fees for Singaporeans/Singapore Permanent Residents (aged 21 years and above)

Full-time Fees

Semester Graduate Certificate Fees
1 Management of Business Analytics Project
Business Analytics Practice
S$3,700.06
S$4,675.90
1 Customer Analytics
or
Big Data Engineering & Web Analytics
S$2,833.36
or
S$3,391.90
1 Capstone Project S$5,350.00
Semester 1 Fees = S$8,375.96 + Selection + Capstone Project
2 Practical Language Processing
or
Specialised Predictive Modelling & Forecasting
S$4,258.60
or
S$3,391.90

Part-time Fees

Semester Graduate Certificate Fees
1 Management of Business Analytics Project S$3,700.06
2 Business Analytics Practice S$4,675.90
3 Capstone Project S$5,350.00
3 Customer Analytics
or
Big Data Engineering & Web Analytics
S$2,833.36
or
S$3,391.90
4 Practical Language Processing
or
Specialised Predictive Modelling & Forecasting
S$4,258.60
or
S$3,391.90
  1. Adjustments will be made for course modules or certificates already taken
  2. Other certificate combinations may be possible by attending both Saturday and Weekday classes, and/or by extending study period
  3. All graduate certificate fees include charges for Practice Module

Applicants must possess the following pre-requisites:

  • Bachelor's degree preferably in Mathematics, Statistics, Econometrics, Management Science, Operational Research, Science or Engineering and a grade point average of at least B
  • Proficiency in the English Language (written and spoken)*
  • Have passed an entrance test
    • NUS-ISS may, at its discretion, accept GRE general test in lieu of NUS-ISS entrance test in genuine cases e.g. a candidate lives in a country where NUS-ISS does not administer entrance tests or candidate had valid reasons that prevented him/her from attending the NUS-ISS entrance test when it was administered
    • A sample of the entrance test can be found here
  • Preferably two years relevant working experience
    • IT, engineering and scientific professionals would make ideal candidates
    • Candidates with highly relevant degrees in Mathematics, Statistics, Econometrics, Management Science, Operational Research or similar, with consistently good academic records may be granted a work experience waiver
  • Have received a favourable assessment at admissions interview conducted by NUS-ISS

 

*English Language Proficiency

  • Applicants who graduated from universities where English is not the medium of instruction should submit TOEFL (Test of English as a Foreign Language) or IELTS (International English Language Testing System) score as evidence of their proficiency in the English language.

TOEFL

Paper-based test (580)
Computer-based test (237)
Internet-based test (85)

IELTS

Result of 6.0

  • Institution code of NUS-ISS for TOEFL is 2432
  • TOEFL and IELTS are only valid for five years after the test and the validity should not expire before the beginning of the application period for the coursework programme.

How to Apply

All applicants are required to submit an online application for our graduate coursework programme (through-train).  

Step 1:     You can refer to our detailed step-by-step guide on how to complete the online application.

Step 2:     It will take you about 30 minutes or more to complete your application.  You will need the softcopies of the supporting documents for your online application.  Click here for the supporting documents to be uploaded and additional information required.

Step 3:     You can proceed to apply online.  Remember to upload all the required supporting documents under the “Documents Upload” section before you do the online submission.  You can refer to our FAQ.

Step 4:     Please ensure you submit your online application(s) and make online payment for the application fee (non-refundable) of S$50.00 per application (inclusive of prevailing GST).

 Important: 

  1. Applications that are incomplete, including missing supporting document(s), will not be processed.
  2. Applicants who are found to have given inaccurate or false information will be required to withdraw from the programme.
  3. All payments for application fee are non-refundable
  4. Please note that the University has not engaged any external agencies to undertake student recruitment on its behalf.Candidates interested in our graduate programmes are advised to apply directly to the University and not through any agents.Candidates who apply through agents will not have any added advantage in gaining admission and the University reserves the right to reject such applications without giving reasons.

Find your fit with new opened doors

There is opportunity in Singapore in almost all industries which are rapidly working towards digital transformation and data analytics sits in the heart of it. What you learn in terms of analytics skills is not as important as what you do with it. It is the attitude and the ability to learn from mistakes, and to contribute back to the company that you work for that is likely to make more of a difference than specific analytics skills.

There are two main paths for advancement in analytics - either technical or managerial. Technical means you continue to deepen your technical area in a domain (Finance, Government, Manufacturing, Telecom, Transportation, Technology companies etc.) and you become an expert data scientist in those areas. The other is managerial, where you can focus on designing solutions for clients (internal or external) to achieve their organization goals in the areas of profit maximization, automation or digitization.

Our internship companies often tell us that if we can give them good students as interns, it is very likely they will get a job offer at the end of the internship.

As an MTech EBAC graduate, you will be prepared for specialist, expert and leadership roles in enterprise business analytics to create business value through strategic use of data, visualisation methods, modelling techniques and frontline tools.

Career Prospects

  • Business Analytics Manager
  • Data Scientist and Architect
  • Business Analyst
  • Optimisation Strategy Consultant
  • Business Intelligence and Performance Management Consultant
  • Enterprise Intelligence Manager
  • Market Intelligence Analyst
  • CRM Data Analyst
  • Risk Analyst
  • Marketing Analyst
  • Big Data Analyst

MTech alumni are pursuing their careers at these global organisations:

  • Accenture
  • Creative Technology
  • DBS Bank
  • Defence Science & Technology Agency
  • Deutsche Bank AG
  • Fuji Xerox Asia Pacific
  • HP Singapore
  • IBM Singapore
  • Infocomm Development Authority of Singapore
  • Inland Revenue Authority of Singapore
  • Jurong Port
  • Microsoft
  • Murex
  • NCS
  • NEC Asia Pacific
  • NTUC
  • OCBC Bank
  • Revolution Analytics
  • Singapore Telecommunications
  • Standard Chartered Bank
  • Starhub
  • ST Electronics
  • Tata Consultancy Services

The NUS-ISS Career Services Office helps students to match jobs based on their skills and experience. There will be bi-yearly Career Fairs held for students and graduates to network with employers. However, successful employment will depend on the employers.

The average starting salary of an analytics professional depends on the degree and your previous working experience. For fresh graduates with no work experience, the starting salary ranges from S$4,000 to S$4,500. Graduates with more than 3 years of work experience can expect a starting pay of S$6,000 and above.

The most important skill is to get the job done and be persistent. You need to be broad-based and the technology does not matter.

You can get some salary benchmarks from these sites:

Learning Journey

 

 

Analytics Project Management and Delivery

Data Analytics Process and Best Practices
Data Story Telling
Data Governance & Protection
Managing Business Analytics Projects
Graduate Certificate in Management of Business Analytics Project
 

Core Analytics Techniques

Statistics Boot Camp
Predictive Analytics – Insights of Trends and Irregularities
Text Analytics
Recommender Systems
Graduate Certificate in Business Analytics Practice
 

Customer Analytics

Customer Analytics
Advanced Customer Analytics
Campaign Analytics
Graduate Certificate in Customer Analytics
 

Big Data Processing

Feature Engineering & Analytics using IOT Data
Graph & Web Mining
Big Data Engineering for Analytics
Graduate Certificate in Big Data Engineering & Web Analytics
 

Practical Language Processing

Text Analytics
New Media and Sentiment Mining
Text Processing using Machine Learning
Conversational Interfaces
Graduate Certificate in Practical Language Processing
 

Advanced Predictive Modelling Techniques

Service Analytics
Generalized Predictive Modeling & Forecasting
Health Analytics
Graduate Certificate in Specialised Predictive Modelling & Forecasting

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