SNAIC AI Programme
Powered by NVIDIA Deep Learning Institute modules and expert faculty, this six‑month, full‑time applied AI programme fast‑tracks learners from fundamentals to industry impact. Receive a monthly stipend during the programme, graduate with a job‑ready portfolio and a Certificate of Attainment.
About Course
AI is transforming every industry, and Singapore needs skilled practitioners who can bridge theory and practice, and cutting-edge technology with real-world applications.
The SNAIC AI Programme, developed in collaboration with the Infocomm Media Development Authority (IMDA), is a six-month, full-time applied AI training programme featuring NVIDIA Deep Learning Institute modules.
Supported under the TechSkills Accelerator (TeSA*) initiative, learners will gain expertise in modern AI domains, including Large Language Models (LLMs), Generative AI, Agentic AI, MLOps, and AI safety.
The programme comprises:
- Two months of immersive, instructor-led training based on modules developed by SNAIC and enhanced with NVIDIA Deep Learning Institute content, equipping participants with the latest AI tools and techniques through hands-on labs and guided projects
- Four months of real-world, hands-on projects with industry partners under the supervision of SNAIC experts and faculty, enabling participants to solve actual business challenges using AI and build a portfolio that demonstrates their capabilities.
* TechSkills Accelerator (TeSA) is a national initiative by Singapore’s Infocomm Media Development Authority (IMDA) to build a future-ready ICT workforce for Singapore’s digital economy. For more information, visit IMDA’s website.
Skills you’ll gain
AI and Machine Learning
Programming and Software Development
Competency-based Education
Computer Ethics and Privacy
Who Should Attend
This programme is ideal for individuals who aspire to build or advance a career in Artificial Intelligence, particularly in applied, engineering-focused roles. It is designed for:
Individuals with experience or familiarity in programming, data handling, engineering workflows, or computational problem‑solving, who are ready to deepen their expertise in modern AI systems such as LLMs, Generative AI, RAG, and Agentic AI.
Individuals with strong technical aptitude and a keen interest in AI, seeking a structured pathway into AI engineering roles.
Professionals looking to transition into AI-focused careers or upskill in advanced AI domains, especially those with experience in technical, analytical, or software‑related roles.
Early-career technologists who want hands-on, project-based experience to accelerate their AI readiness and build a strong portfolio.
Prerequisites
- Eligible for both Singaporean and PR
- Ability to commit to a six-month, full-time schedule, including daily in-person sessions and a team-based industry project.
- Basic Python programming knowledge, including variables, control structures, functions, and data handling.
- Recognised degree; or diploma in a relevant discipline with a minimum of two years of relevant work experience.
Learning Outcomes
Upon completing the programme, learners will be able to apply a comprehensive set of AI competencies that span foundational knowledge, advanced model development, engineering workflows, and responsible deployment practices.
Competencies graduates will be equipped with:
- Design advanced AI solutions by synthesising machine learning and data engineering approaches to justify model choices, assess performance trade-offs, and address complex real-world problem contexts.
- Operationalise and govern AI systems by implementing reproducible pipelines and MLOps practices to ensure reliable deployment, monitoring, and lifecycle management of production-grade AI solutions.
- Design and evaluate advanced deep learning and intelligent AI architectures by analysing training dynamics, system behaviour, and performance trade-offs to justify architectural decisions for complex application contexts.
- Design and govern agentic AI systems by integrating reasoning, retrieval, and tool use to manage performance, reliability, and control limitations in advanced AI deployments.
- Evaluate multimodal AI system designs by analysing visual and speech-based models, assessing performance, robustness, and failure modes in complex real-world application contexts.
- Design trustworthy AI deployment strategies by integrating safety, verification, and assurance frameworks to justify deployment readiness, risk mitigation, and responsible use in high-impact environments.
Teaching Team
Soh Cheng Lock, Donny
Associate Professor / Prog Leader, Infocomm Technology, Singapore Institute of Technology
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Zhang Zhengchen
Associate Professor, Teaching & Learning (T&L) Lead, Infocomm Technology Cluster, Singapore Institute of Technology
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Mahesh Raveendranatha Panicker
Associate Professor, Singapore Institute of Technology
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Xu Bingjie
Assistant Professor, Singapore Institute of Technology.
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Tong Rong
Assistant Professor, Infocomm Technology, Singapore Institute of Technology
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Ian McLoughlin
Professor, Infocomm Technology, Singapore Institute of Technology
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Daniel Wang Zhengkui
Associate Professor, Director of SNAIC, Director of DSAIL, Singapore Institute of Technology
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Lou Xin
Associate Professor, Singapore Institute of Technology
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Course Details
Schedule
| PHASE | DURATION | FORMAT & Venue | Timing | TOPICS / DESCRIPTION |
|---|---|---|---|---|
| AI Foundations | Months 1–2 (8 weeks) | Full-time, in‑person at SIT Punggol Campus | Mon – Fri, 9AM – 5PM | Intensive hands‑on training which includes NVIDIA DLI modules and daily lab work on these topics:
|
| Industry Attachment Project (IAP) | Months 3–6 (16 weeks) | Full-time, on‑site with industry partners | Mon – Fri, 9AM – 6PM | Four months of Industry Attachment Project in teams of 4–5, supervised by SIT/SNAIC faculty and industry experts. Full-time (9AM to 6PM) participation, weekly check‑ins, demos, and continuous project milestones. Learners work on real business problems and deliver end‑to‑end AI solutions. |
Enrolment Process & Timeline
| Milestone | date |
|---|---|
| Application Period | January 2026 - March 2026 |
| Candidate Assessment & Interview | February 2026 - April 2026 |
| Offers Sent to Selected Candidates | May 2026 |
| Programme Commencement | June 2026 |
Note:
Enrolment into the programme is subject to candidates meeting all eligibility criteria and successfully completing the required selection processes. Eligible candidates who pass all selection requirements will be enrolled strictly on a first‑come, first‑served basis, and placement is not guaranteed until registration is confirmed.
Certificate
A Certificate of Attainment will be issued to participants who:
- Attend 100% of the course; and
- Undertake and pass assessments during the course
Participants who meet the attendance requirement but do not pass the assessments will receive a Certificate of Participation.
As the structure of this course requires participant's consistent on-site presence during standard working hours on every standard workday, all absences must be supported by valid documentation and subject to approval to be considered for meeting the attendance requirement.
Assessment
The programme incorporates continuous, hands‑on assessments to ensure learners build strong technical capabilities and can apply AI concepts in real-world contexts. Assessment components include:
- Daily Labs & Practical Exercises
Learners will complete guided labs across modules such as Python & Machine Learning, Deep Learning, Computer Vision, LLM Fine-Tuning, RAG & Agentic Systems, Data Engineering/MLOps, and AI Safety. These labs assess correctness, code quality, analysis, and practical application.
- Quizzes & Knowledge Checks
Short quizzes in selected modules test conceptual understanding of AI models, architectures, and engineering principles.
- Mini Projects
Modules such as Deep Learning, Computer Vision, and LLM Fine‑Tuning require learners to complete short, end‑to‑end projects that demonstrate model implementation, experimentation, evaluation, and presentation.
- Industry Attachment Project (IAP)
The final four months are assessed through a substantial team‑based industry project, including progress demos, technical implementation, documentation, and final presentation. Learners are evaluated on problem‑solving, engineering rigor, model performance, responsible AI considerations, and communication of results.
Fee & Stipend
One-time Enrollment Fee: S$1,090
Monthly Stipend for Participants: S$4,000
Note:
- All fees above include GST. GST applies to individuals and Singapore-registered companies.
For Organisations
Interested in this course for your business or team?
Tailored to your organisation's specific training needs, we can help you design and develop custom courses to grow key talent and build specialist expertise to meet the future demands of work.
Frequently Asked Questions
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What is the total duration of the programme?
The programme runs full‑time for six months, comprising two months of intensive AI training followed by a four‑month Industry Attachment Project.
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What is the class schedule like?
During the first two months, classes run Monday to Friday, 9am–5pm, with hands‑on labs and practical sessions. The following four months are dedicated to a full time 9am to 6pm Industry Attachment Project.
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Who is this programme suitable for?
The programme is ideal for degree or diploma holders in technical disciplines, working professionals looking to transition into AI roles, and early‑career technologists seeking hands-on applied AI experience.
If you are motivated to deepen your technical AI capabilities, can commit full‑time for six months, and want to work on real-world projects that build industry‑ready skills, this programme is well suited for you.
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What are the entry requirements?
Applicants should have:
- Basic knowledge of Python programming; and
- Either a recognised degree, or a diploma in a relevant field with at least two years of relevant work experience.
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Are participants paid a stipend during the programme?
Yes. Participants will receive a monthly stipend of S$4,000 throughout the six‑month programme. This stipend supports full-time commitment during both the training phase and the Industry Attachment Project.
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What kinds of projects will I work on?
Learners will work on real-world applied AI problems with industry partners, guided by SIT/SNAIC faculty. Projects span areas such as computer vision, multimodal AI, LLM fine‑tuning, RAG systems, and industrial AI applications.
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Will I receive a certificate upon completion?
Participants who attend 100% of the course and pass the non‑credit‑bearing assessments will receive a Certificate of Attainment.
Those who meet the attendance requirement but do not pass the assessments will receive a Certificate of Participation.
All absences must be supported by valid documentation (e.g., medical certificate, official letter). -
Are there additional certifications included?
Yes. The programme incorporates selected modules from the NVIDIA Deep Learning Institute (DLI), enabling participants to earn industry‑recognised NVIDIA certificates (depending on module completion).
Course Info-Session
8 February 2026, 7-8PM, Live Online with Q&A
Interested in the SNAIC AI Programme and want to fully understand what the six‑month journey entails?
Join our live online Course Info‑Session to hear directly from A/Prof Donny Soh, Programme Lead, as he walks you through the curriculum, industry project expectations, learner experience, and what it takes to succeed in this full‑time programme.
Whether you're exploring a career transition into AI or strengthening your technical foundation, this session will help you determine if the programme is the right fit for your goals.
Come prepared with questions—there will be a live Q&A segment.
2 February 2026 (Monday)
7:00PM – 8:00 PM (SGT)
Live Online
Zoom (Link will be provided upon registration)
Course Runs
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