Program Overview

Overview of University Programs

The university offers a range of programs designed to build capabilities in infocomm and digital business. These programs are categorized into several 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 Programs

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

The university offers stackable programs as an alternative pathway to continuing education without disrupting one's career. These programs include:

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

Blended Learning Programs

The Blended Learning Programs provide individuals with the flexibility to learn over their own time and pace while achieving their academic and career goals. These programs include:

• About
• Programmes
• Digitalisation Passport

Corporate Programs

The university works with organizations to provide contextualized workplace training or customized learning experiences for their employees. These programs include:

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

Data Science Solutions Implementation

This course is designed to equip data scientists with the skills to deploy Data Science and Artificial Intelligence (DSAI) models in real-world environments. The course covers:

• DSAI Project Tasks
• Implementation Considerations
• Cloud Technologies with workshop
• Container Technologies and CI/CD pipeline
• Deployment considerations
• Real Life Deployment Challenges
• Effective Communication
• Technical Writing

The course is targeted at individuals who develop DSAI models and are looking to gain hands-on knowledge of how to deploy such models. The course is also suitable for leaders of DSAI teams who want to be aware of what is required in a DSAI model deployment.

Prerequisites

Participants should have prior experience in:

• Strong coding foundation in programming languages such as R, Python, etc. (mandatory)
• Familiarity with IDEs such as RStudio, Anaconda, Google Colab, etc.
• Experience in creating data science or artificial intelligence models
• Comfortable in installing 3rd party software such as Docker, streamlit, etc. without supervision
• Experience in leading or involved in DSAI projects

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. Dave HO and Dr. Rita CHAKRAVARTI.

Course Resources

The course is part of the Data Science Series and an essential component of MTech, Capstone offered by NUS-ISS starting 2022. Participants can also access additional resources, including the Executive Education Planner (2025) and Executive Education Planner (2026).