Program Overview

Overview of University Programs

The university offers a range of programs designed to build capabilities in infocomm and digital business. These include Executive Education Programmes, Graduate Programmes, Stackable Programmes, Blended Learning Programmes, and Corporate Programmes.

Executive Education Programmes

Executive Education Programmes are designed to build capabilities in infocomm and digital business. The programmes cover various disciplines, including:

• Artificial Intelligence
• Cybersecurity
• Data Science
• Digital Agility
• Digital Innovation & Design
• Digital Strategy & Leadership
• Digital Products & Platforms
• Digital Sustainability
• Digital Health
• Software Systems
• StackUp - Startup Tech Talent Development

Graduate Programmes

The university offers five practice-based graduate programmes focusing on information technology (IT) and data science. These programmes include:

• Graduate Diploma in Systems Analysis
• Master of Technology in Artificial Intelligence Systems
• Master of Technology in Digital Leadership
• Master of Technology in Enterprise Business Analytics
• Master of Technology in Software Engineering

Stackable Programmes

Stackable Programmes provide an alternative pathway to continuing education without disrupting one's career. The programmes include:

• Graduate Certificates in:
  • Data Science
  • Digital Solutions Development
  • Artificial Intelligence
  • Smart Systems & Platforms
• Professional Certificates in:
  • Digital Leadership
  • Health Service Innovation
• Professional Diploma in:
  • Health Service Transformation

Blended Learning Programmes

Blended Learning Programmes provide individuals with the flexibility to learn over their own time and pace while achieving their academic and career goals. The programmes cover:

• About Blended Learning
• Programmes
• Digitalisation Passport

Corporate Programmes

Corporate Programmes work with organisations to provide contextualised workplace training or customised learning experiences for employees. The programmes include:

• Corporate Digitalisation
• Active Learning for Problem Solving
• International Programmes
• Digital Academy Services
• Internship & Job Placements
• Skills For Transformation Programme

Product & Pricing Analytics Course

The Product & Pricing Analytics course leverages predictive and prescriptive analytics for decision intelligence. The course covers:

• Introduction to analytics, trends, and developments for Product and Pricing Excellence
• Experimental design techniques for product innovation and optimisation
• Econometrics and Pricing Analytics
• Prescriptive Analytics and Decision Science Techniques
• Decision Science for Product and Price Optimisation
• Inventory Planning and Simulation

Key Takeaways

At the end of the course, participants will be able to:

• Apply experimental design methods for concept testing, factor screening, rapid experimentation, and optimisation for connected and sustainable products
• Understand basic economic concepts and apply econometrics for product & pricing analysis
• Learn and implement decision science techniques for product and pricing optimisation
• Apply strategy and methods for inventory optimisation and simulation
• Build data collection, analytics, and decision-making capabilities and solutions with IoT technologies
• Integrate machine learning and analytics into edge computing to build a more connected world and perform decision-making

Who Should Attend

The course is applicable for professionals engaged in the following areas:

• Product Analyst
• Pricing Analyst
• Commercial Excellence Analyst
• Sales/Marketing Analyst

Prerequisites

Participants should have:

• Some prior years of experience working within planning teams in an organisation
• A strong interest and knowledge in basic predictive modelling
• Familiarity with R/Python
• Completed the Statistics Bootcamp II and Predictive Analytics - Insights of Trends and Irregularities prior to attending this course

What to Bring

No printed copies of course materials are issued. Participants must bring their internet-enabled computing device (laptops, tablet, etc.) with power charger to access and download course materials.

Certificate

A Certificate of Completion will be issued to participants who meet a minimum attendance rate of 75% and pass the assessment.

Instructors

The course is taught by experienced instructors, including Mr. Brandon NG and Ms. Christine CHEONG.

Course Resources

The course is part of the Data Science Series offered by NUS-ISS, providing an intermediate pathway to the ISS portfolio in the Data Science Graduate Certificate in Specialised Predictive Modelling & Forecasting syllabus.