Advanced Deep Learning for Computer Vision (Synchronous E-learning)
About This Course
Advanced Deep Learning for Computer Vision is an advanced technical programme designed to equip learners with the knowledge and applied capabilities to analyse, design, and assess modern computer vision systems used in industrial and enterprise environments.
The course follows a structured progression from system-level understanding to data representation, processing, feature extraction, deep learning methods, and advanced video analytics. Learners examine how business requirements, architectural constraints, and deployment contexts influence the selection and design of vision technologies across edge and cloud environments.
Through a strong emphasis on interpretation, comparison, and system-level reasoning, the programme prepares learners to make informed technical decisions when working with image- and video-based AI solutions under real-world constraints.
What You'll Learn
Analyse industrial computer vision requirements to determine how business use cases and vision system concepts influence the selection of appropriate vision technologies.
Design applied vision system architectures by integrating architectural components and system design patterns in computer vision solutions.
Design, develop and evaluate edge-based and cloud-based vision systems by applying appropriate deployment models and communication protocols to optimise system performance, scalability and latency.
Design and implement feature extraction and representation methods for image and video data using appropriate feature extraction and representation techniques in vision systems.
Deconstruct image and video processing techniques to explain how filtering, transformation, and analysis methods affect data quality and suitability for vision applications.
Compare global and local feature description approaches to explain how statistical, geometrical, and learned representations support visual understanding.
Design and apply deep learning–based methods for object segmentation, detection and recognition in vision systems.
Design and apply advanced video analytics algorithms for activity tracking, scene understanding and high-level video analytics in vision systems.
Entry Requirements
Age: 25 years and above
Education: At least a GCE 'O' Level certificate/ GCE ‘N’ Level (Normal Academic stream), Nitec or Higher Nitec qualifications. Applicants without formal academic qualifications may also be considered if they have relevant work experience and computer knowledge
Digital Proficiency: Comfortable using digital tools and workplace software (e.g., Microsoft Excel, cloud-based platforms). Able to perform basic computer tasks such as internet search, creating folders, and copy-paste operations
Technical Experience: No coding experience is required