About Course
Quantum computing is rapidly moving from theory to industrial application. As global investments accelerate and cloud-based quantum hardware becomes accessible, demand is growing for professionals who can translate quantum concepts into practical solutions. Classical systems face limitations in optimisation, simulation, and cryptography — areas where quantum algorithms show strong potential.
This course equips learners with the technical foundations and hands-on expertise to design, implement, and validate quantum algorithms for real-world use. Integrating mathematics, physics, and computer science with applied development, the programme prepares participants for quantum software engineering and applied innovation.
Through laboratory-based learning and an industry-aligned project, you will prototype and test quantum solutions using platforms such as Qiskit. You will develop competencies in algorithm design, computational thinking, and technology integration — preparing you to contribute to quantum R&D and emerging Industry 4.0 ecosystems across finance, logistics, healthcare, and beyond.
About the Pathway
This course is part of the Quantum Computing Development Programme, that equips learners with quantum computing foundations and practical development skills, progressing from theory and programming to hands‑on laboratory experimentation to prepare learners for entry-level roles.
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2 | Quantum Computing Development: Laboratory |
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Skills you’ll gain
AI and Machine Learning
Data Science and Analytics
Systems Engineering
Cloud Computing
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Who Should Attend
This course is suitable for:
Early‑career technical professionals seeking to build new expertise in advanced computation.
Mid‑career engineers, developers, and researchers looking to pivot into or expand into quantum computing.
Graduate‑level learners and researchers who need deeper applied knowledge of quantum concepts.
Job functions including software engineers, data scientists, algorithm developers, systems architects, and R&D staff across computing, finance, healthcare, energy, and logistics.
Professionals involved in next‑generation solutions, advanced modelling, or computational innovation across all industries where quantum advantage may emerge.
Minimum Entry Requirements
- A bachelor’s degree (or equivalent qualification) in Computer Science, Engineering, Physics, Mathematics, or a closely related discipline.
- Familiarity with linear algebra (vectors, matrices, eigenvalues), probability, and basic complex numbers.
- Basic programming experience in Python or another high-level language.
- For applicants without a strong quantitative background, evidence of equivalent industry experience in data science, software engineering, or related technical domains may be considered.
- Participants will need to be enrolled in Quantum Foundations and Algorithms as a prerequisite.
Learning Outcomes
By the end of the course, participants will be able to:
Explain core quantum computing principles, including qubits, superposition, entanglement, and quantum gates, and relate them to computational advantage over classical systems.
Formulate computational problems suitable for quantum approaches, particularly in optimisation, simulation, and secure data processing contexts.
Design and implement quantum circuits using development frameworks such as Qiskit, translating algorithms into executable quantum programs.
Simulate, execute, and validate quantum algorithms on cloud-based quantum platforms; interpret measurement outputs and evaluate performance constraints.
Apply error mitigation techniques and assess limitations of current noisy intermediate-scale quantum (NISQ) devices.
Integrate quantum solutions within broader digital and Industry 4.0 ecosystems, identifying opportunities for hybrid classical–quantum workflows.
Collaborate in project-based development environments to prototype industry-aligned quantum applications addressing real-world challenges.
Communicate technical findings through structured documentation and presentations that translate quantum concepts into actionable business and R&D insights.
Teaching Team
Dr David Sanan
Assistant Professor, Singapore Institute of Technology
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Dr Vivek Balachandran
Associate Professor, Infocomm Technology, Singapore Institute of Technology
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Dr Chetan Waghmare
Head of Education Outreach – Quantum Computing, Accelequant
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Course Details
Learning Hours
Total: 60 hours
- Classroom Facilitated Training: 30 hours
- Asynchronous E-Learning: 24
- Assessment: 6 hours
Certificate and Assessment
A Certificate of Attainment will be issued to participants who:
- Attend at least 75% of the course
- Undertake and pass non-credit bearing assessment during the course
Participants who meet the attendance requirement but do not pass the assessment will receive a Certificate of Participation.
Assessment Plan
Mode of Assessment: Practical Exam
Fee Structure
The full fee for this course is S$7,854.00.
| Funding Category | Eligible Funding | Course Fees Payable After Funding |
|---|---|---|
| Singapore Citizen (Below 40) | 70% | S$2,356.20 |
| Singapore Citizen (Above 40) Funded under SkillsFuture Mid-Career Enhanced Subsidy (MCES) | 90% | S$915.10 |
| Singapore PR / LTVP+ Holder | 70% | S$2,356.20 |
| Non-Singapore Citizen | Not Eligible | S$7,854 |
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.
Course Runs
Learning Pathway
Earn specialist certificates through micro-credentials in the following CSM pathways. Stack these micro-credentials towards a bachelor's degree at SIT.
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