Introduction
This course introduces the fundamentals of real-time signal processing using Digital Signal Processor (DSP) and Very Large-Scale Integration (VLSI) architecture. It emphasises the core concept of real-time processing and covers various software and hardware approaches for processing signals in real time. Learners will be able to integrate theory and practice to develop sophisticated DSP and VLSI solutions, and apply principles of Optimum general-purpose DSP and VLSI system design, including associated trade-offs. This course is ideal for engineers and data scientists looking to innovate in Artificial Intelligence (AI), digital communications, and smart system design. As this micro-credential course is only offered in the FlexiMasters in Signal Processing and Machine Learning programme, learners are required to enrol into the programme and complete all required courses within this programme.This course is credit-bearing (3 AU) and stackable to:
- Graduate Certificate in Signal Processing and Machine Learning (9 AU)
- FlexiMasters in Signal Processing and Machine Learning (15 AU)
- MSc in Signal Processing and Machine Learning (30 AU)
Learners will receive their Statement of Accomplishment (for a grade of D and above) or Certificate of Participation for this course—dependent upon their assessment performance.
This course is part of the FlexiMasters in Signal Processing and Machine Learning.
Note: Shortlisting will be conducted.
Course Availability
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Date(s): 10 Aug 2026 to 02 Jan 2027
Venue: Nanyang Technological University
Registration Closing Date: 13 Jul 2026
At the end of the course, learners will be able to:
- Explain the theoretical principles of signal processing systems, such as finite precision, sampling and quantisation.
- Compare and evaluate different architectures for implementing hardware systems for real-time processing.
- Design basic software solutions using Digital Signal Processor (DSP) processor for real-time system design.
Suitable for practicing engineers, hardware and software designers, data scientists, R & D managers, and industry planners who seek an understanding of current approaches and evolving directions for DSP and AI technologies. It is also intended for engineers and data scientists who anticipate future involvement in these areas.
As the micro-credential courses are only offered in this FlexiMasters in Signal Processing and Machine Learning programme, learners are required to enrol into this programme and complete all required courses within this programme.
Note: Shortlisting will be conducted.
Standard Course Fee: S$5615.68
| SSG Funding Support | BEFORE funding & GST | AFTER SSG funding (if eligible under various schemes) & 9% GST |
| Course Fee | Course Fee Payable | |
| Singapore Citizen (SC) and Permanent Resident (PR) (Up to 70% funding) | $5,152 | $1,684.70 |
| Enhanced Training Support for SMEs (ETSS) | $5,152 | $654.30 |
| Singapore Citizen aged ≥ 40 years old SkillsFuture Mid-career Enhanced Subsidy (MCES) (Up to 90% funding) | $5,152 | $654.30 |
- NTU/NIE alumni may utilise their $1,600 Alumni Course Credits for this course. Click here for more information.
- Learners can utilise their SkillsFuture Credits for this course.
- Singaporeans aged 40 years and above are able to use their SkillsFuture Credit (Mid-Career) top-up of $4,000 to offset the course fee after SSG funding.
- Natural Language Processing (3 AU)
- Analytic & Ensemble Machine Learning (3 AU)
- Genetic Algorithms & Machine Learning (3 AU)
- Video Analysis and Processing (3 AU)
