

Effective from AY2024/25 Trimester 2 (January 2025), the Postgraduate Certificate in Data Engineering and Smart Factory will be retired. For more details, please refer to the full notice here.
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.
"This course enabled me to better understand future trends in the smart factory and build better rapport with each other."Yeoh Wee Chye-
"Course was really interesting and fundamental enough for an individual to understand and start exploring the world of Artificial Intelligence."Macalino Noel MinjootElectromechanical System Integrator, WaveScan Technologies
Chief Innovation & Trust Officer, Amaris AI
Prof Yu Chien Siang is the Chief Innovation & Trust Officer for Amaris AI, an AI startup that offers full stack AI as a service and is currently also Professor (ICT) at SIT. He was the Chief Innovation Officer (CIO) of a department in the Ministry of Home Affairs and later of Certis Cisco. In this role, he pioneered and developed new AI systems, i.e. embedded AI for low power and low cost edge systems, led a Malware and IoT Security Lab, as well as a Robotics and Drones Lab. Prior to this, he was the most senior Computer Security Consultant at the Singapore government. He was awarded the Carl Duisberg Gesellschaft Scholarship to pursue his studies at a German university and graduated as a Data Systems Engineer. During his study, he received training at the Siemens Research Laboratory and IBM R&D Laboratory in Boblingen. He has been working in the Civil Service since 1981 and was awarded National Day Honours, the Public Administration Medal (Silver) in 1993 and (Silver) Bar in 2004. He was also given the Cyber Security Hall of Fame in 2018, an inaugural professional category award from AISP and supported by the Cyber Security Agency. He has been active in the fields of IT leadership, innovation development and its related cultural transformation and IT Security for more than 30 years. During this time, he led numerous national-level IT projects in information security such as the Electronic Road Pricing (ERP), Standard Operating Environment (SOE) etc., IoT security via the ANSES project and homeland security, developing workflow and people identification operational systems. He was instrumental in evolving many advanced systems architecture used in the public service and the fundamental mechanisms required for their large systems rollout. He invented unique low cost smart card readers, strong cryptographic systems, more efficient protocols and fault tolerant designs. He was also a pioneer in robotics cum drone and AI hacking and new ideas like adaptive security (Liquid Defence) and Security by Design. In addition, he is teaching a series of AI courses, titled Eureka!AI for C-suite and modern cyber security for CISOs at NUS and the undergraduate course on “Introduction to Cyber Crime”, but now renamed as “Introduction to Cyber Security” in his capacity as Adjunct Associate Professor at the Department of Mathematics of the National University of Singapore. He is member of the Singapore government’s Cyber Security Advisory Group and was an ex-President of the Singapore Microcomputer Society, a pioneer in the exploitation of microcomputers and a regular speaker at government events, being the founder of the Governmentware show. He has also been one of the judges for the RSA Innovation Sandbox since 2014. He is currently a member of ITSC, worked on ISO security standards and was involved in the early days of the AISP.
Course Run | Dates | Time |
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April – May 2024 Run | 9, 17, 24 April & 8, 15, 21 and 29 May 2024 | 9:00 am – 6:00 pm |
A Certificate of Attainment will be issued to participants who
Participants who meet the attendance requirement but do not pass the assessment will receive a Certificate of Participation.
The full fee for this course is S$5,886.00.
Category | After SF Funding |
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Singapore Citizen (Below 40) | S$1,765.80 |
Singapore Citizen (40 & Above) | S$685.80 |
Singapore PR / LTVP+ Holder | S$1,765.80 |
Non-Singapore Citizen | S$5,886.00 (No Funding) |
Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.
New Engineering Micro-credentials Launching Soon!
Exciting news! We are introducing new micro-credentials in Electrical and Electronic Engineering & Infrastructure and Systems Engineering. Be among the first to know by registering your interest today! Register now →