Introduction
This course is designed to equip learners with comprehensive knowledge in video analysis and processing. It includes principles, concepts and theories behind image and video compression techniques and standards, Artificial Intelligence (AI) models used for video analytics, key video analytics tasks and applications, as well as recent developments in the field. Learners interested in expanding their expertise in video analytics are encouraged to enroll. Upon completion, learners will possess the theoretical understanding and practical insights necessary to advance their careers in video analysis and processing.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
-
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 key image compression techniques and standards and assess their impact on image quality and processing efficiency.
- Evaluate various key video compression techniques and standards.
- Analyse the core artificial intelligence models for video analytics
- Describe some common video analysis tasks and explain their applications.
- Evaluate recent and emerging developments in video analysis and processing, assessing their potential applications, limitations, and implications in real-world deployment.
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.
- Real-time DSP Design & Applications (3AU)
- Natural Language Processing (3 AU)
- Analytic & Ensemble Machine Learning (3 AU)
- Genetic Algorithms & Machine Learning (3 AU)
