Introduction
According to a 2024 Forbes study on AI trends, the global AI market was valued at $136.55 billion in 2022, expected to grow at a compound annual growth rate of 37.3% from 2023 to 2030, reaching $1,811.8 billion by 2030. Singapore is one of the fastest-growing markets for AI talent in Asia-Pacific, with AI talent hiring rising 14% faster than overall hiring in 2022 (EDB, 2023).
The hybrid learning approach combines online and in-person classes with project-based learning, providing flexibility for career switchers in today’s fast-paced digital economy. Delivered by expert instructors and NTU Faculty, the curriculum covers databases, Python programming, big data engineering, data analytics, and machine learning algorithms to meet the needs of Singapore's employers.
Graduates will gain the expertise and skills necessary for data analyst, data engineer, and data science roles. They will understand fundamental concepts in machine learning, AI, and data science, and be able to implement these principles practically. A portfolio of real-world projects will demonstrate their problem-solving abilities using advanced technologies.
Learners will engage in real-world case studies and capstone projects, addressing actual industry challenges. They will also have access to resources such as discussion groups, and mentorship from seasoned professionals.
In summary, this course offers an exceptional learning opportunity for those seeking a career in AI and data science, equipping learners with the knowledge and skills to thrive in these dynamic industries.
This course is offered on a full-time (3.25 months) and part-time (5 months) basis.
Upon successful completion of this course, learners will be awarded an Advanced Professional Certificate.
Due to high demand, applications for this course may close sooner than expected. Hence, prospective learners are advised to submit their application as soon as possible.
| Join us at the SCTP I'm-possible Insight Series: Connecting Today's Learning to Tomorrow's Careers in Data Science and AI | |
The I’m-possible Insight Series is a series of programme-specific info sessions tailored for individuals aiming to navigate their way into high-demand tech career roles. Meet our trainers and career consultants and gain insights on how to turn the challenge of a career transition into a well-mapped path to success with SCTP. | |
| Date & Time : 28 May (Wed), 12:15 PM | Register Now |
Course Availability
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Date(s): 01 Jul 2025 to 22 Nov 2025
Time: Weekdays: 7:00PM to 10:00PM, Weekends: 9:00AM to 4:00PM (Part-Time)
Schedule: Download here
Venue: Virtual (Online), NTU e-Learning Platform & NTU@one-north
Registration Closing Date: 10 Jun 2025
Outline
| Module Title | Synopsis |
| Foundations of Data Science: Python and SQL | Learners will understand database basics, SQL, and Python libraries for data science, including data modeling, advanced SQL, data transformation with Numpy and Pandas, exploratory data analysis, and data visualisation. |
Scalable Data Solutions: Big Data Engineering Essentials | Learners will build and manage large-scale data pipelines and systems, covering data extraction, transformation, loading, data warehousing, architecture, and distributed data processing. |
Building Intelligent Systems: Machine Learning and Generative AI | This module focuses on developing and deploying machine learning models, covering paradigms, training, testing, deployment, and generative AI for unstructured data like image and text classification. |
| Certified AI Practitioner | Learners will explore AI, ML, and generative AI concepts and applications, including foundation model design, model training, finetuning, and prompt engineering, with real-world use cases across industries. |
Transforming Business with GPT: Hands-On Generative AI Applications | This module teaches creating applications using GPT API technology to improve business outcomes. Learners will understand GPT API at a team or organizational level, including working with, fine-tuning, deploying, and integrating GPT models in the cloud. |
| Full Stack Programming and Deployment of AI Solutions | Learners will develop and deploy full-stack web applications, covering front-end and back-end development, database management, API programming, cloud deployment, project management, and Web3 technologies, gaining hands-on experience with modern technologies. |
Who should attend
A background in IT is not necessary but preferable. This course is designed to cater to the intricacies of data science, data engineering and AI. Hence, individuals with a background in these disciplines bring valuable prior knowledge that will enhance their learning experience and understanding of the curriculum.
Applicants will be required to undergo a shortlisting process where they must share their résumé and complete a pre-course assessment. Our instructors and career consultants will review applicants to assess their suitability before deciding whether to shortlist them for the course.
Fees and Funding
Standard Course Fee: S$32,264
SSG Funding Support | Course fee | Course fee payable after SSG funding, if eligible under various schemes |
BEFORE funding & GST | AFTER funding & 9% GST | |
1 Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | $29,600 | $9,679.20 |
2 SCs aged ≥ 40 years old | $3,779.20* | |
3 SCTP Additional Course Fee Funding Support (ACFFS) (Up to 95% funding) | $3,319.20* |
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
c) Persons with Disabilities.
*The maximum government funding for each module is capped at $7,000, regardless of the specific funding scheme. As a result, certain modules within the course may not be funded up to the typical 90% or 95% levels. This limitation contributes to the slightly higher nett fee. We seek your understanding on this matter.
Trainers
Dr Teoh Teik Toe
Dr Teoh is a Academic Director and Senior Lecturer at Nanyang Business School (NBS), teaching Business Analytics and AI subjects. His other roles include:
- Academic Director of the NBS Master of Science in Business Analytics
- Associate Director of NTU NBS AI Lab and NTU Information Management Research Centre
- Adjunct Professor at Henan University, Shandong Institute of Technology and Han Chiang University
Dr Teoh has published 4 books and more than 100 publications. Additionally, he has more than three decades of research experience in the areas of Big Data, Deep Learning, Cybersecurity, AI, Machine Learning and Software Development. He also possesses more than 25 years of teaching experience in AI, Data Science and Analytics, Statistics, Business, Finance, Accounting and Law.
Dr Teoh obtained his PhD in Computer Engineering from NTU, Doctor of Business Administration and Master of Business Administration from University of Newcastle, Master of Law from the National University of Singapore, and Bachelor of Laws and Master of Laws from University of London. He completed his post doctorate at Singapore University of Technology and Design.
Dr Teoh is a chartered holder of CFA, ACCA, CIMA, CA Singapore, Chartered Tax Practitioner, Associate Chartered Valuer and Appraiser and CPA Australia. Additionally, he is a member of Mensa International.
Akanksha Tiwari
Akanksha is a data scientist and entrepreneur with a robust background in data-driven insights. Currently, she serves as the Co-Founder of Novela, a pioneering simulation platform for professional learning. Under her leadership, Novela has successfully partnered with prestigious institutions such as Columbia Business School, Imperial College London, and University College Dublin.
Prior to her role at Novela, Akanksha held significant positions at renowned companies such as Twitter, Spotify, Rakuten and Adobe in various roles in data science, machine learning, predictive modelling and software engineering. Akanksha has also worked as a data science researcher at the National University of Singapore (NUS) and published a paper on machine learning, data mining and natural language processing on social media data.
Akanksha has extensive experience in algorithms, learning platforms, machine learning, natural language processing, predictive modelling and software development in C++, Java and Python.
Akanksha holds a Master's Degree in Computer Science from NUS.
Dr Ng Yibin
Dr Ng is a highly accomplished data scientist and entrepreneur with a proven track record of developing and deploying impactful data-driven solutions. As the Co-Founder and Chief Data Scientist of EigenAI, a cutting-edge company that leverages data to predict customer behavior, Yibin is at the forefront of applying data science to solve real-world business challenges. EigenAI is funded by Antler and EnterpriseSG. Before EigenAI, Yibin led data science initiatives at Standard Chartered and Uber, providing crucial data science support to operational teams across various continents.
Dr Ng holds a PhD in Electrical and Computer Engineering from Carnegie Mellon University. He has published various research papers in the field of data science, electrical engineering, magnetic storage media and signal processing. He also holds several US patents in cloud computing, hard disk drive and wireless communication networks.
Zane Lim
Mohamed Jawad
Jawad is an accomplished technology leader with more than a decade of experience spanning artificial intelligence, machine learning, and data science. Jawad has held several leadership positions at Gojek, where he served as Head of Data for Gojek Mobility, leading the company's marketplace platform across engineering, product and data functions. He also drove significant technological innovations, including the development of pooled dispatch systems for food delivery and the successful transition from Google Maps to internal tools, substantially improving the unit economics of fulfillment services.
As Head of Data for Gojek Marketplace, he led a team of 30 data scientists and analysts to implement sophisticated machine learning solutions for pricing optimisation, demand modeling, and supply positioning.
Jawad specialises in AWS cloud applications, computer simulations, Bayesian inference, predictive modeling, probabilistic models, recommender systems, statistical modeling, Tensorflow and software development in Java, Python and R.
Jawad holds a Master's degree in Knowledge Engineering from the National University of Singapore.
Germayne Ng
Germayne is a seasoned data scientist with extensive experience in data science, machine learning systems and mapping technologies. Germayne has held several leadership positions at GoTo Group, where he currently serves as Head of Data Science and is responsible for building the company’s mapping data platform.
Germayne drove significant technological innovations, including the development of sophisticated location search systems, routing optimisation, real-time Estimated Time of Arrival prediction systems and sustainable maps platform. Germayne has filed a patent for machine learning and publishes articles on data science on Medium and participates in Kaggle data science competitions in his free time.
Germayne's areas of expertise include artificial intelligence, computer vision, deep learning, machine learning, predictive modelling, reinforcement learning, statistics, Tensorflow and software development in Java, Python and R.
Germayne holds a Master's degree in Computer Science from the Georgia Institute of Technology.
Lai Shumin
Shumin is an experienced practitioner with a strong background in leveraging data to drive business insights and solutions. As a data scientist, she is passionate about applying machine learning and analytical techniques to solve complex problems across various industries. Her experience spans both consulting and in-house roles, providing her with a broad understanding of data science applications.
Shumin holds a Bachelor's degree in Business Analytics from the National University of Singapore, scoring distinctions in Applied Analytics and Business Domain Applications. Her expertise lies in AI Engineering, Applied Analytics Techniques, Machine Learning, Natural Language Processing and Python Programming.
Patrick Fong
Patrick is a Senior Consultant and Instructor at IVT Pte Ltd. He delivers namely cloud computing courses from Amazon Web Services (AWS) and is an expert in VMware products. He has attained many certifications such as AWS Certified Solutions Architect, DevOps Engineering and Machine Learning. Besides AWS products, Patrick is also certified in Servicenow and VMware products.
He was a mentor instructor to qualify new instructors onboarding for VMware and Dell EMC’s training team. With his vast experience from IT infrastructure products such as servers, enterprise storages and virtualisation coupled with years of consulting and project management experience, his trainings are unique and beneficial to students due to his real-life experiences in the field. In his 25 years of teaching and consultancy roles, he has delivered a myriad of courses and projects in Asia, Europe and South America.
Besides being a qualified instructor for AWS, VMware and Servicenow products, he holds an MBA from Heriot Watt University, Edinburgh Business School UK.
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