Master of Technology in Enterprise Business Analytics

Summary

The Master of Technology in Enterprise Business Analytics programme (MTech EBAC) is specifically designed to meet industry demand for data scientists who can help organisations achieve improved business outcomes through data insights. It is best suited for professionals seeking to practise at the entry level and also for upgrading professionals with a suitable professional background (e.g. IT professionals) but lack the necessary academic fundamentals to move into Specialist or Expert positions in Business Analytics.

This programme is jointly offered by NUS-ISS, the Department of Industrial and Systems Engineering and the Division of Engineering & Technology Management of the Faculty of Engineering.

Application for the January 2018 intake will open on 1 February 2017.
Next Intake: Jan 2018
Duration: Full-time 1.5 years (3 semesters)

Part-time 2.5 years (5 semesters)
Application Deadline:
  • 31 Aug 2017 (Overseas applicants)
  • 15 Sep 2017 (Local applicants)

Fees

Full-time

Singaporeans, Singapore Permanent Residents and International Students
Subtotal (per semester) S$15,005.72
$14,700.00 - Semester Tuition Fee
$305.72 - Semester Miscellaneous Fee

Part-time

Singaporeans, Singapore Permanent Residents and International Students
Subtotal (per semester) S$7,551.52
$7,350.00 - Semester Tuition Fee
$201.52 - Semester Miscellaneous Fee

Programme Details

  • Overview
  • Modules
  • Projects & Internships
  • Timetable & Exams
  • Fees & Loans
  • 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 and supply chain management.

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 targeting marketing campaigns
  • 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 techniques to develop high-performance analytics capability
  • Translate massive and complex unstructured data 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:

  • Core Courses - Pass 4 compulsory Core Courses
  • Basic Elective Courses - Pass 8 Basic Elective Courses
  • Advanced Elective Courses - Pass 3 Advanced Elective Courses
  • Team-based Internship or Off-site Project

Core Courses (Compulsory)

Foundations of Business Analytics

In this module students will be introduced to foundational Statistical Analysis & Business Analytics techniques. These include data visualization, descriptive statistics, data sampling, hypothesis testing, correlation analysis and predictive modelling using linear and logistic regression techniques.  You will learn the best practices and methodologies for managing and undertaking business analytics projects including data acquisition, data cleaning and pre-processing, model testing and deployment, data governance and project management. You will be introduced to statistical software tools like R & SPSS. 
Pre-requisites: Nil

 

Data Analytics

This module comprised two parts:
In part A, students will learn how to build and apply advanced predictive models. Methods and techniques studied will include generalized linear models (GLM), Multinomial Logistic Regression, decision tree learning and artificial neural networks.  The skills learned include selecting appropriate modelling techniques and combining models in various ensemble architectures.

In part B, students will learn essential forecasting and time-based prediction techniques. These will range from simple time-series methods such as moving average, exponential smoothing and linear/non-linear curve fitting to more advanced methods including decomposition methods, stationary/non-stationary time series analysis, autoregressive integrated moving average (ARIMA) models, transfer function models and cox proportional hazards regression methods for survival analysis.
Pre-requisites: EB5101 Foundations of Business Analytics

 

Advanced Analytics

This module comprised two parts:
In part A, students will learn advanced statistical modelling and machine learning methods. You will learn how dimension reduction techniques, segmentation and profiling can be used for long term strategy formulation. You will also learn how Bayesian methods can be applied to data analytics and how market basket analysis, association mining and collaborative filtering can be used to mine user data to discover insights and make product and content recommendations. 

In part B, students will learn essential business intelligence and data visualisation skills. This will include data visualisation concepts and best practices as well as business dashboard design and implementation.  You will also learn the differences between relational and non-relational databases as well as the skills for querying and reporting from them.
Pre-requisites: EB5101 Foundations of Business Analytics

Decision Making and Optimisation

This course aims to equip students with the knowledge and skills to solve and optimise business problems that involve a large number of constraints and variables. Techniques, including linear programming, the transportation model, network models, goal programming, non-linear programming and inventory models will enable you to address a wide range of applications in healthcare, logistics, defence, transportation, logistics and economics.
Students will learn how to formulate a model for the business problem, by identifying the decision variables, objective function and constraints. They will then learn how to validate their model, determine the optimal solution perform sensitivity analysis, and interpret the results, and make recommendations for decision making.
Pre-requisites: EB5101 Foundations of Business Analytics

Basic Elective Courses

Choose any 4 from Business Analytics Techiniques

  • Campaign Management
  • Customer Relationship Management
  • Web Analytics
  • New Media and Sentiment Mining
  • Supply Chain Analytics
  • Service Analytics
  • Clinical Healthcare Analytics


Choose any 4 from these study areas:

Advanced IT Management

  • Managing IT Outsourcing & Subcontracting
  • Business Process Management
  • Agile Software Project Management
  • Advanced Software Estimation

IT Infrastructure Technology

  • Information System Security
  • Cloud Computing
  • Internet of Things Technology

Knowledge Engineering Techniques

  • Computational Intelligence I
  • Computational Intelligence II
  • Text Mining
  • Case Based Reasoning
  • Sense Making and Insight Discovery

Requirements, Design & Construction

  • Software Requirements Engineering
  • Digital User Experience Design
  • Object Oriented Design Patterns
  • Architecting Software Solutions

Software Development Platforms & Technologies

  • Enterprise .Net
  • Enterprise Java
  • Enterprise Integration
  • Mobile Wireless Solution Design

Technopreneurship & Innovation

  • Independent Work I
  • Independent Work II
  • Digital Innovation and Design
Click here for a detailed write-up on Basic Elective Courses


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

Student projects for MTech EBAC students extend over a period of eight months for full-time students and one year for part-time students. Full-time students are allowed to conduct their project as a team-based internship if desired. The expected commitment for the project is 60 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

EBAC_Full-time Timetable

Timetable & Exams for Part-time Students

EBAC_Part-time Timetable

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 core and elective course.

Students who fail a core course will be asked to withdraw. A minimum average grade across all examinations must be achieved to be awarded the degree. Students who do not fulfil the minimum requirements of the degree may be considered for the award of the postgraduate Diploma in Enterprise Business Analytics.

Exemptions for examinations may be granted for up to four basic electives, provided students have at least the equivalent of an NUS or NTU 2nd Upper Class Honours degree, and have passed the same or similar subjects at either a Masters or PhD level.


The fees above are for the Academic Year 2016 / 2017.

Fees are correct at time of posting and are subjected to changes without prior notice. The University reserves the right to alter the fees at any time. Fees for subsequent years are under review.

What Do Miscellaneous Fees Cover?

Miscellaneous fees are typically levied on items that are either not covered or partially covered by tuition fee and grant/subsidy. All students, whether registered on a full-time or part-time basis, are charged the mandatory miscellaneous fees. These are due at the same time as the tuition fees. These fees help defray the costs of student activity, health services and insurance, campus shuttle service and other services.

Any queries about fees and payment, please contact us at issfinance@nus.edu.sg.

Loans and Subsidies

Students who require financing for their tuition fees may apply for the following:

  • ISS Student Assistance Loan Scheme
  • SkillsFuture Credit

Read up more on the above loans and subsidies

Applicants must possess the following pre-requisites:

  • Bachelor's degree preferably in 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
    • Candidates who possess highly relevant Honours/Masters/PhD degrees may be granted entrance test waiver
    • ISS may, at its discretion, accept GRE general test in lieu of ISS entrance test in genuine cases (eg: a candidate lives in a country where ISS does not administer entrance tests or candidate had valid reasons that prevented him/her from attending the ISS entrance test when it was administered
    • A sample of the entrance test can be found here
  • Preferable have 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 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

Note: 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 apply online for our graduate coursework programme. Please note that you will be redirected directly to NUS’ Online Application System.

Step 1: Please click here to read the instructions before you proceed to apply online.

Step 2: Proceed to NUS’ Online Application System to apply

Step 3: Payment of Application Fee

Application Fee (non-refundable) – S$20.00 (inclusive of prevailing GST)

Note: Please pay your application fee (S$20.00) online via the Graduate Admission (GDA2) System. Print out a copy of the payment receipt and attach it with your application as proof of payment. Alternatively, you can also make payment in cheque or bank draft (made payable to “National University of Singapore”) and attach the Application Fee Form.

You should write your name, application number, identity/passport number and telephone numbers (home & office) on the reverse side of the cheque/bank draft.

Any further queries about payment, please contact us at issfinance@nus.edu.sg

Step 4: Submission Checklist

After submitting your application via the online Graduate Admission (GDA2) System, the completed online application form should be printed out and submitted to the School together with the supporting documents listed below. All documents which are to be submitted should preferably be in A4 size. All documents which are not in English must be accompanied by an official certified English translation. Omission of required information and documents may render the application void.

Supporting documents

  1. Online Application form (printed from the system after the online submission), duly declared and signed
  2. A recent coloured passport-sized photograph to be attached in the box provided in the Online Application form.
  3. MTechForm
  4. A copy of the following documents :
    • Degree scroll
    • Detailed result transcript of academic records from each university, polytechnic or college attended
    • A copy of professional certificates (if applicable)
    • A copy of the TOEFL/ IELTS score report
    • A copy of citizenship certificate, identity card, passport or documentary proof of permanent residence status, where applicable
    • A copy of Employment Pass for international applicants working in Singapore
  5. Testimonials from the employer (where relevant)
  6. The Cheque/ Bank Draft & Application Fee Form OR Proof of Payment of Application Fee (e.g. E-Receipt)

You will be asked to produce the originals for verification during enrolment (if your application is successful).

Please send the application form along with the supporting documents or submit them personally to:

Master of Technology Course Administrator
Institute of Systems Science
National University of Singapore
25 Heng Mui Keng Terrace
(off Pasir Panjang Rd)
Singapore 119615

IMPORTANT NOTE:
Completed application forms must be submitted with the supporting documents and an application fee of S$20.00. Incomplete applications (e.g. those with insufficient documents or have not satisfactorily completed their requirements for the bachelor's degree by the stipulated deadline of submission) and applications received after the closing date, will not be processed.

If you need to make changes or updates to your application after the online submission, please email isspostgrad@nus.edu.sg to inform us of the changes.

Step 5: Checking your status of application

After the application deadline, all received applications will be processed, and the online application status in the Graduate Admission System will be updated to "physical application verified" within 14 days.

Invitation to sit for the aptitude test & interview will be sent by email to the email address provided in the application form.

Results of your application will be made known to you through postal mail about 2 months after the application closing date. You can also check your application outcome results via the online admission system 2 months after the application closing date. If you do not hear from us two months after the deadline, please email isspostgrad@nus.edu.sg

Applicants who are unsuccessful in their application will need to submit a new application together with all the relevant supporting documents if they are interested to be considered for the programme again in the next intake.

Note:
Due to the large number of applicants seeking admission, we are sorry we will not be able to attend to enquiries on the status of applications or receipt of documents. If you are concerned about the delivery of your documents, you may wish to consider sending them via registered mail or courier.

Important: 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 for most areas of IT. What you learn in terms of IT 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 IT skills.

There are two main paths for advancement in IT - either technical or management. Technical means you continue to deepen your technical area in a domain (such as system architecture, or software engineering, etc.) and you become an expert in those areas. The other is management, where you can focus on project management, outsourcing, etc.

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, analytics, models 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
  • 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
  • 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 IT professional depends on the degree and your previous working experience. For fresh graduates with no work experience, the starting salary ranges from S$3,600 to S$3,800. Graduates with more than 3 years of work experience can expect a starting pay of S$4,000 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:

Your Learning Journey

Term 1

4 CORE COURSES (Compulsory)

  • Foundations of Business Analytics
  • Data Analytics
  • Advanced Analytics
  • Decision Making and Optimisation
Term 2

8 BASIC ELECTIVE COURSES

  • Choose 4 courses from the Business Analytics Techniques Group:
    • Campaign Management
    • Customer Relationship Management
    • Web Analytics
    • Analytics for Logistics Management
    • Analytics for Tourism and Hospitality
    • Analytics for Pharmaceutical Professions
  • Choose 4 courses from other study groups
Term 3

3 ADVANCED ELECTIVE COURSES

Choose 3 courses offered by:

  • Institute of Systems Science
  • NUS Faculty of Engineering
    • Department of Industrial & Systems Engineering
    • Division of Engineering & Technology Management
Term 4

Team-based Internship or Off-site Project

Gain deeper industry insights and apply what you have learnt to real-life work environments.

  • Practise newly-acquired technical skills through a real-life consulting engagement

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