Course Overview

Modular Certification Course
1+ months
Fee Subsidy
Up to 90% SF Funding

Most AI Deep Learning and data science projects fail, despite promising test results and clear problem statements at the start.

This is because many users may start off with unrealistic expectations due to an inadequate understanding of AI; what it can and cannot do, and IT managers may fail to understand the privacy, ethics, cyber security, and governance issues related to this new disruptive science. Additionally, there may not be enough high-quality data available, and users do not understand the importance of garbage in, garbage out. 

The aim of this module is to provide a business deployment perspective of foundational Deep Learning AI capabilities, ranging from Natural Language Processing to Machine Vision; in a manner that requires little or no coding. Neural networks and how Deep Learning works, the data input requirements, project lifecycle, and the development framework would be introduced. What problems each specific AI algorithm can solve would be illustrated in an interactive workshop session and the enterprise benefits would be highlighted via case studies; e.g. enhanced productivity for corporate decision-making, process automation, or difficult unattended problem-solving.

The focus is on rapid prototyping and guiding the users and the relevant project team members to validate project viability using the data and requirements that are available. Importantly, you will gain the skills to highlight missing gaps, and failure scenarios and to discuss AI compliance, privacy, and cyber security requirements at the design phase, avoiding misunderstanding of the project’s complexity and hence be able to protect the project from failure.

Finally, modern challenges such as ensuring man-in-the-loop AI oversight, cyber security hardening against adversarial AI attacks, and privacy obligations would be covered as new requirements for an upgraded corporate IT risk management framework that will be instrumental in protecting the company’s digitalisation efforts.

The future of AI continues to shine brightly, and we aim to highlight major high-value factory automation future possibilities as AI and Big Data systems converge pervasively, and 5G and IoT AI at the edge become commodity. With these insights, you will master key leadership skills to manage and plan AI projects successfully and hence, deliver strategic benefits to the corporation.

Who Should Attend

  • Engineers and Project Managers of factory and automation systems
  • Professionals with work exposure to manage automation projects or are managing factory innovation deployments, capabilities and associated risks
Haja Mydin
"This course enabled me to better understand future trends in the smart factory and build better rapport with each other."
Yeoh Wee Chye
Haja Mydin
"Course was really interesting and fundamental enough for an individual to understand and start exploring the world of Artificial Intelligence."
Macalino Noel Minjoot
Electromechanical System Integrator, WaveScan Technologies

What You Will Learn

  • The architecture, applications and operations of popular AI Deep Learning systems and how they would benefit smart factory via enhanced productivity in corporate decision-making, process automation and problem-solving
  • Overview of software development using AI frameworks
  • Overview of Natural Language Processing (NLP) AI systems and key applications
  • Overview of AI vision processing systems for object recognition, segmentation, pose, biometrics and action recognition
  • Overview of AI Ethics, governance, AI cyber security vulnerabilities such as Adversarial Attacks, data security, privacy and common implementation weaknesses. Understand privacy and cyber security best practices for AIOps and the need for ethics, transparency and fairness for Trustworthy AI
  • Overview of AI Project Management and leadership roles
  • State-of-the-art in AI, future trends and developments; new pending problems that can be solved with better algorithms and the cost reduction expected as the technology advances
  • Analyse the feasibility of user requirements, data input requirements, AI project life cycle and deployment suitability for Smart Factory

Teaching Team

Yu Chien Siang
Yu Chien Siang

Chief Innovation & Trust Officer, Amaris AI

View profile


Course Run Dates Time
November - December 2023 Run  1, 8, 15, 22 & 29 November, 6 & 13 December 2023 (Every Wednesdays) 9:00 am - 6:00 pm


Certificate and Assessment

A Certificate of Participation will be issued to participants who

  • Attend at least 75% of the module
  • Undertake non-credit bearing assessment during the module

A Certificate of Attainment will be issued to participants who

  • Attend at least 75% of the module
  • Undertake and pass credit bearing assessment during the module

Fee Structure

The full fee for this course is S$5,832.00.

Category After SF Funding
Singapore Citizen (Below 40) S$1,733.40
Singapore Citizen (40 & Above) S$653.40
Singapore PR / LTVP+ Holder S$1,749.60
Non-Singapore Citizen S$5,832.00 (No Funding)

Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.

Course Runs

There are no upcoming course runs at the moment.

Subscribe to our mailing list to learn about the latest dates as soon as they become available.


Learning Pathway


Earn a Postgraduate Certificate

The Postgraduate Cetificate in Data Engineering and Smart Factory is designed to equip engineers for greater business competitiveness amidst the exponential growth in robotic automation, information and communication technologies.

Explore More arrow--right