School of Continuing & Lifelong Education
Coursework Programmes
Master of Science (Industry 4.0)
The MSc (Industry 4.0) is an inter-disciplinary programme offered in collaboration with the Faculty of Engineering, Faculty of Science, School of Computing and Institute of Systems Science, NUS Business School and School of Continuing and Lifelong Education.
The MSc (Industry 4.0) programme will enable student to attain, by the time of graduation:
- Breadth in ability to understand technology core concepts from a management viewpoint, including key emerging technology and business areas
- Understanding of key business and processes, including supply chain management, systems design and change management
- Ability to use both breadth and depth to be more effective functional specialists, or to move up management ranks
- Ability to drive change and transformation projects in a company, through technical understanding, understanding of business processes, and effective leadership
Both full-time and part-time studies are offered. The period of candidature are as follows:
- Full-time studies can be completed in 12-18 months. The maximum candidature is 24 months.
- Part-time studies can be completed in 18-36 months. The maximum candidature is 36 months.
Candidates must satisfy the following requirements to be conferred the degree of MSc (Industry 4.0):
- Complete a minimum of 40 MCs with 20 MCs in essential core modules and 20 MCs in graduate certificates and elective modules;
- Complete and pass the programme requirement of at least one Graduate Certificate listed under “List of Modules” below;
- Obtain a minimum CAP of 3.00; and
- Satisfy any other additional requirements that may be prescribed by the Programme Management Committee for MSc (Industry 4.0), or the University.
Modules are generally 4 MCs, except when otherwise stated.
- Essential Core Modules (20MCs)
- IND5001 Introduction to Industry 4.0 and Applications
- IND5002 Digital Physical Integration in Industry 4.0
- IND5003 Data Analytics for Sense-making
- IND5005A Professional Career Development
- IND5005/IND5005B Industry Consulting and Application Project
- Graduate Certificates & Elective Modules:
All required electives must be completed for the award of the graduate certificate that will be issued by the respective faculties. In addition to the graduate certificate, candidates may select any elective offered to meet the 40-MC graduation requirement.
| Faculty | Module Title | MCs |
| FoE |
Graduate Certificate in Additive Manufacturing (Choose 6 modules) | 12 |
| ME5608A Principles and Processes of Additive Manufacturing
ME5608B Hybrid Manufacturing ME5615A Design and Pre-processing for Additive Manufacturing ME5615B Post-processing for Additive Manufacturing ME5614A Special Project in Additive Manufacturing ME5513A Fatigue Analysis for Additive Manufacturing MLE5301 Metallic & Ceramic Materials in Additive Manufacturing MLE5302 Polymer Materials in Additive Manufacturing |
2
2 2 2 2 2 2 2 |
|
| Graduate Certificate in Internet of Things (Choose 5 modules) | 10 | |
| EE5020 Data Science for Internet of Things
EE5021 Cloud Based Services for Internet of Things EE5022 Cyber Security for Internet of Things EE5023 Wireless Networks EE5024 Sensor Networks EE5060 Sensors and Instrumentation for Automation EE5061 Industrial Control and IEC Programming EE5027 Statistical Pattern Recognition EE5026 Machine Learning for Data Analytics EE5025 Intellectual Property: Innovations in IoT |
2
2 2 2 2 2 2 2 2 2 |
|
| Graduate Certificate in Robotics and Automation (Choose 5 modules) | 10 | |
| EE5060 Sensors and Instrumentation for Automation
EE5061 Industrial Control and IEC Programming EE5062: Autonomous Systems EE5063: Modelling of Mechatronic Systems EE5064: Dynamics and Control of Robotic Manipulators EE5065: Tenets of AI in Robotics ME5405A: Machine Vision Fundamentals ME5408: Kinematics of Robot Manipulators ME5607: Smart Factories |
2
2 2 2 2 2 2 2 2 |
|
| FoS | Graduate Certificate in Data Mining and Interpretation | 8 |
| ST5227 Applied Data Mining
DSA5203 Visual Data Processing and Interpretation |
4
4 |
|
| Graduate Certificate in Deep Learning for Industry | 8 | |
| DSA5102 Foundations of Machine Learning
DSA5204 Deep Learning and Applications |
4
4 |
|
| Graduate Certificate in Quality Assurance and Yield Optimization (Choose 2 modules) |
8 | |
| ST5203 Design of Experiments for Product Design and Process Improvements
ST5208 Analytics for Quality Control and Productivity Improvements ST5212 Survival Analysis ST5210 Multivariate Data Analysis |
4
4 4 4 |
|
| BIZ | Graduate Certificate in Digital Supply Chain | 12 |
| IND5021 Managing the Digital Supply Chain
IND5022 Data Analytics for Smart Manufacturing DOS5101A Managing the Financial Supply Chain IND5024 Strategic Procurement in a Digital World |
4
4 2 2 |
|
| SoC | Graduate Certificate in Principles and Practice of Secure Systems (Choose 3 modules) | 12 |
| CS5322 Database Security
CS5332 Biometric Authentication CS5331 Web Security CS5321 Network Security CS5439 Software Security |
4
4 4 4 4 |
|
| Graduate Certificate in Digital Business (Choose 3 modules) | 12 | |
| IS5007 Strategising for Global IT-enabled Business Success
IS5116 Digital Entrepreneurship IS5117 Digital Government IS5151 Information System Security Policy and Management |
4
4 4 4 |
|
| ISS |
Graduate Certificate in ISY5002 Pattern Recognition Systems | 13 |
| Graduate Certificate in ISY5004 Intelligent Sensing Systems | 10 |
One intake is admitted every year to start in Semester 1 (i.e. August) of the academic year. The recommended study schedule for full-time and part-time studies are illustrated as below.
| Full-time Study Schedule | |
| 1st Year of studies, Sem 1: | Core Modules (12 MCs) Preallocated three 4-MC modules Elective Modules (8 MCs) |
| 1st Year of studies, Sem 2: | Core Modules (8 MCs) Preallocated core and Capstone modules Elective Modules (12 MCs) |
| Special Term Part 1 | Core Modules (4 MCs) Capstone modules |
| Part-time Study Schedule | |
| 1st Year of studies, Sem 1: | Core Modules (12 MCs) Preallocated three 4-MC modules |
| 1st Year of studies, Sem 2: | Core Modules (4 MCs) Preallocated module Elective Modules (8 MCs) |
| Special Term Part 1 | Core Modules (4 MCs) Preallocated Capstone modules |
| 2nd Year of studies, Sem 1: | Core Modules (4 MCs) Preallocated Capstone module Elective Modules (4 MCs) |
| 2nd Year of studies, Sem 2: | Elective Modules (8 MCs) Select from 2-MC and 4-MC modules |
Master of Science (Venture Creation)
The MSc (Venture Creation) is an inter-disciplinary programme offered in collaboration with the NUS Enterprise, NUS Business School, Faculty of Engineering, Faculty of Science, School of Computing and Yong Loo Lin School of Medicine.
Designed to transform mindsets and accelerate translation of ideas into solutions, the programme targets aspiring entrepreneurs wanting to launch new ventures with success by providing mentorship in business development and access to NUS technologies, as well as opportunities to network for market access
Only full-time studies are offered. The period of candidature is as follow:
- Full-time studies can be completed in 12-18 months. The maximum candidature is 24 months.
Candidates must satisfy the following requirements to be conferred the degree of MSc (Venture Creation):
- Complete a minimum of 40 MCs with 28 MCs in essential core modules and 12 MCs in elective modules;
- Attain a minimum CAP of 3.00; and
- Satisfy any other additional requirements that may be prescribed by the Programme Management Committee for MSc (Venture Creation), or the University.
- Essential Core Modules (28MCs):
- TR3301 Summer Programme in Entrepreneurship
- TR5302 Experiential Entrepreneurship Internship
- TR5049 Lean Startup Practicum
- BMS5405S New Venture Creation
- Elective Modules:
| Faculty | Module Title | MCs |
| Business-related | BMS5103 Entrepreneurial Strategy
BMS5104 Current Trends in Growth Markets BMS5105 Strategy and Big Data BMS5107 Ethical Leadership and Corporate Strategy BMS5108 Macroeconomics and Finance: Perspectives from Asia BMS5109 Strategy: Bridging the Planning – Implementation Divide BMS5110 Managerial Economics BMS5111 Legal Issues in Business BMS5113 Venture Capital BMS5114 Asian Business Environment BMS5115 Strategic Negotiations BMS5202 Global Supply Chain Management BMS5203 The Knowledge & Innovation Economy 4.0 BMS5204 Cross-Border Business Management in the Digital Age BMS5205 Business Analytics BMS5206 Business Analytics with R BMS5302 International Finance BMS5303 Valuation and Mergers & Acquisitions BMS5304 Selected Topics in Finance: Private Equity BMS5305 Entrepreneurial Finance BMS5306 International Financial Management BMS5307 Financial Markets and Institutions BMS5308 Personal Finance and Wealth Management BMS5309 Investment Banking BMS5310 Financial Management of Family Business BMS5311 Corporate Finance BMS5404 Becoming Future Prepared Global Leaders BMS5406 Asian Leadership BMS5407 Workplace and Corporate Deviance BMS5502 Marketing Practice & Impact BMS5503 Pricing BMS5504 Marketing Analysis and Decision Making BMS5505 Marketing in a Digital Age BMS5506 Consumer Behaviour BMS5507 Behavioral Economics BMS5508 Design Thinking & Business Innovations BMS5509 Consumer Culture Theory BMS5510 Marketing Strategies in the New Economy BMS5511 Sustainability Marketing BMS5602 Business Analysis and Valuation BMS5702A Asian Management and Leadership: Learning From Zheng He BMS5702B Managing Business Networks |
4
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 |
| Management of Technology-related | MT5007 Management of Technological Innovation
MT5006/IE5211 Strategic & New Product Development MT5010 Technology Intelligence & IP Strategy MT5911 Venture Funding |
4
4 4 4 |
| Technology-related | CS5228 Knowledge Discovery and Data Mining
CS5242 Neural Networks and Deep Learning CS5272 Embedded Software Design CS5321 Network Security CS5322 Database Security CS5331 Web Security CS5339 Theory and Application of Machine Learning CS5421 Database Applications Design and Tuning CS5422 Wireless Networking CS5424 Distributed Database CS5425 Big Data Systems for Data Science CS5439 Software Security DSC5221A Managing the Financial Supply Chain EE5020 Data Science for Internet of Things EE5023 Wireless Networks EE5026 Machine Learning for Data Analytics EE5027 Statistical Pattern Recognition EE5060 Sensors and Instrumentation for Automation EE5061 Industrial Control and Programming IND5001 Introduction to Industry 4.0 & Applications IND5002 Digital Physical Integration in Industry 4.0 IND5003 Data Analytics for Sense-making IND5004 Digital Infrastructure and Transformation IND5021 Managing the Digital Supply Chain IND5022 Data Analytics for Smart Manufacturing IND5024 Strategic Procurement in a Digital World IS5003 Platform Design and Economy IS5004 Enterprise Architecture IS5005 Digital Engagement IS5006 Intelligent System Deployment IS5007 Strategising for Global IT-enabled Business Success IS5116 Digital Entrepreneurship IS5117 Digital Government IS5126 Hands-on with Applied Analytics IS5128 Digital Innovation IS5151 Information System Security Policy & Management IS5152 Data-Driven Decision Making IS5451 Pervasive Technology Solutions and Development MDG5227 Bio-Innovation & Entrepreneurship MDG5236 Pathways to Biomedical Innovation and Enterprise MDG5237 Biomedical Innovation Capstone* ME5513A Fatigue Analysis for Additive Manufacturing ME5614A Special Project in Additive Manufacturing ME5615B Post-processing for Additive Manufacturing MLE5301 Metallic & Ceramic Materials in Additive Manufacturing MLE5302 Polymer Materials in Additive Manufacturing ST5227 Applied Data Mining |
4
4 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 4 4 4 4 4 4 2 4 4 4 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 4 |
*subject to approval
The inaugural cohort will be admitted to start in Semester 2 (i.e. January) of the academic year AY2020/2021. The recommended study schedule is illustrated as below.
| Full-time Study Schedule | ||
| 1st Year of studies, Sem 2 AY2020/2021: | Core Modules (8 MCs) Preallocated one 8-MC module |
Core Modules (4 MCs) Preallocated one 4-MC moduleElective Modules (4 MCs) Select from 2-MC and 4-MC modules |
| 1st Year of studies, Special Term Part 1 AY2020/2021: | Core Modules (4 MCs) Preallocated one 4-MC module |
|
| 1st Year of studies, Special Term Part 2 AY2020/2021: | Core Modules (12 MCs) Preallocated one 12-MC module |
|
| 1st Year of studies, Sem 1 AY2021/2022: | Elective Modules (8 MCs) Select from 2-MC and 4-MC modules |
|