Program Overview

Overview of the Master of Technology in Enterprise Business Analytics Programme

The Master of Technology in Enterprise Business Analytics (MTech EBAC) programme is designed to meet the industry's pressing need for adept data scientists and machine learning specialists, with a keen focus on their role in advancing enterprises through the power of data and AI. This programme provides holistic training in key aspects of data science and AI, from exploratory data analysis and predictive modelling to natural language processing, recommender systems, and big data engineering.

Programme Structure

The MTech EBAC programme is structured to equip professionals with the essential technical expertise to harness data, machine learning, and enabling technologies to develop and deploy effective data-driven solutions. These solutions are designed not only to enhance decision-making processes but also to optimise operations, drive profitability, and elevate overall user experiences within enterprises.

Recognition and Awards

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

Programme Objectives

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
• Automating production fault detection in manufacturing using predictive modelling

Learning Outcomes

The programme aims to help enterprises move towards a stronger emphasis on computer tools and statistical and machine learning techniques to develop high-performance analytics capability. It also aims to translate massive and complex unstructured data into insights, produce predictive models to solve a broad range of problems across various business functions and units, and contribute to the development of more effective business strategies and plans for sustainable growth and competitive advantage.

Study Awards and Scholarships

• NUS-ISS ASEAN Merit-Based Study Award: A partial scholarship initiative launched to enhance NUS-ISS's visibility across ASEAN countries (excluding Singapore) while supporting deserving students from developing nations to pursue full-time Master's programmes at NUS-ISS in Singapore. This merit-based award covers 40% of the tuition fees.
• IMDA Post Graduate Scholarship: The SG Digital Scholarship (Postgraduate) is an industry scholarship that empowers students pursuing tech or media-related studies at the Masters or PhD level.

SkillsFuture Level-Up Programme

Singaporeans aged 40 and above can receive a SkillsFuture Credit enhanced subsidy top-up of $4,000 through the SkillsFuture Level-Up Programme. The subsidy can be used to offset the course fees.

Programme Details

Duration

• Full-time: 1 year (2 semesters)
• Part-time: 2 years (4 semesters)

Application Timeline

• Applications for January 2026 admissions into the Part-Time MTech EBAC programme should be submitted before 15 November 2025.
• Applications for August 2026 admissions into the Full-Time MTech EBAC programme will commence on 1 October 2025 and should be submitted before 1 April 2026.

Entrance Test / GRE

• Face-to-Face: 19 November 2025 (Last ET) | 6 January 2026
• Applicants based in Singapore are to take the entrance test in NUS-ISS. Applicants based overseas are required to submit their GRE scores in place of the Entrance Test.

Courses

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

• Fundamental - Complete 2 Graduate Certificates
• Specialist - Complete 2 of 5 Graduate Certificates

Fundamental Analytics Areas

Analytics Project Management

• Statistics for Business II
• Data Storytelling
• Data Management for Analytics
• Managing Business Analytics Projects

Business Analytics Practice

• Data Analytics Process and Best Practice II
• Statistics in Action: Driving Data Insights
• Predictive Analytics – Insights of Trends and Irregularities
• Text Analytics

Specialist Analytics Areas

Customer Analytics

• Customer Analytics
• Advanced Customer Analytics
• Campaign Analytics

Big Data Analytics

• Big Data Engineering for Analytics
• Recommender Systems
• Processing Big Data for Analytics

Practical Language Processing

• Text Processing using Machine Learning
• New Media and Sentiment Mining
• Conversational UIs
• Text Analytics

Specialised Predictive Modelling & Forecasting

• Complex Predictive Modelling & Forecasting
• Product & Pricing Analytics
• Analytics for Commercial Excellence

Intelligent Financial Risk Management

• Advanced Machine Learning for Financial Services
• Explainable & Responsible AI for Finance
• Credit Risk Modelling and Analytics
• Alternative Data for Fintech Innovation

Capstone Project & Internships

• A central element of the MTech programme is the project module.
• Student projects for MTech EBAC students will include intense full-time engagement of 5 months with companies for full-time students. For part-time students, the capstone engagement will be for 7-12 months.

Timetable & Exams

Timetable & Exams for Full-time Students

Timetable & Exams for Part-time Students

Admission & Application

Admissions Criteria

• Bachelor's degree preferably in Mathematics, Statistics, Econometrics, Management Science, Operational Research, Science, or Engineering and a grade point average of at least B
• Demonstrate proficiency in the English Language (written and spoken)
• An acceptable GRE score (overseas applicants) or pass NUS-ISS Entrance Test
• Have received a favourable assessment at admissions interview conducted by NUS-ISS
• Preferably two years of relevant working experience

How to Apply

All applicants are required to submit an online application for our graduate coursework programme (through-train) through GDA3.

Career Pathways

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 Career Progression

MTech alumni are pursuing their careers at global organisations such as 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, and Tata Consultancy Services.

Testimonials

• Luthfi Nur Afifah, Senior Engineer, Micron Technology: "The MTech EBAC programme transformed me into a confident analytics solution developer and communicator, equipping me with the technical and strategic skills to build impactful solutions and align them with business goals."
• Ang Rui Xiang, Analysis Executive, MINDEF: "I decided to enrol in the MTech EBAC programme as the skills taught are highly applicable in various job markets where analytics is increasingly being recognised and utilised."
• Thirupura Sundaram Shanmugam, Data Science Consultant, GBee.ai, Tulasea Inc.: "My experience with the MTech EBAC programme was enriching, blending theory with real-world application and fostering collaboration among peers."
• Zhang Tao, Executive Director, Business Analytics, Standard Chartered Bank: "The MTech EBAC programme was enriching, with practical coursework directly applicable to my work challenges, and bolstered my confidence in technical decision-making and honed my skills in advanced analytics and Generative AI."
• Muhammad Hyqel Bin Razali, Data Quality Analyst, UOB: "The MTech EBAC programme equipped me with practical skills and hands-on experience, allowing me to apply data governance frameworks effectively and drive business value in my role."