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Introduction
The objective of this course is to introduce the basic concepts, applications and recent advances of mainstream visual recognition and image understanding techniques. This course will cover the topics of image classification, semantic segmentation, object detection and vision and language modeling.
- Graduate Certificate in Data Science and Artificial Intelligence
- Graduate Certificate in Artificial Intelligence and AI Plus
- Graduate Certificate in Artificial Intelligence and AI Ethics
- FlexiMasters in Data Science and Artificial Intelligence-
- FlexiMasters in Artificial Intelligence and AI Ethics
- FlexiMasters in Certificate in Artificial Intelligence and AI Plus
At the end of the course, learners are able to:
1. understand the main theory and technical design of computer vision systems, including classification, detection, segmentation, and multimodal modeling;
2. design simple prototype systems in the above domains and;
3. Write research proposals about the. above domains
Image Classification
- Foundations of deep learning
- Overview of modern network architectures for image classification
Semantic Segmentation
- Overview of mainstream semantic segmentation networks
- Recent advances in semantic segmentation
Object Detection
- Overview of the mainstream object detectors: R-CNN, Fast/Faster/Mask RCNN, SSD
- Advanced topics in proposal-free methods.
Vision and Language
- Modeling
Overview of Image Captioning, VQA, and Visual Dialog
- Advanced topics in Referring Expression Grounding and Language Pre-training
For learner who wish to acquire the knowledge and skills to boost their career prospects, become savvier in technology applications as well as better equipped for the fast paced advancements expected ahead.
Standard Course Fee: S$1,944
SSG Funding Support | Course fee payable after SSG funding, if eligible under various schemes | ||
Fee BEFORE funding & GST | Fee AFTER funding & 8% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | S$1,800.00 | S$583.20 | |
Enhanced Training Support for SMEs (ETSS) | S$223.20 | ||
SCs aged ≥ 40 years old | |||
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
FlexiMasters in Data Science and Artificial Intelligence
| COURSE TITLE | ACADEMIC UNIT |
| CET787 Foundations of Computation Thinking and Programming | 1 |
| CET788 AI 1:AI Foundation | 1 |
| CET789 AI 2: Reinforcement Learning | 1 |
| CET790 AI 3: Computational Game Theory | 1 |
| CET791 ML1: Supervised learning: Bayesian decision theory and classifiers | 1 |
| CET792 ML2: Supervised learning: Non-probabilistic classifiers | 1 |
| CET793 ML3: Unsupervised learning | 1 |
| CET794 AI Ethics 1: Foundations of AI Ethics | 1 |
| CET795 AI Ethics 2: AI Ethic Standardization | 1 |
| CET800 AI Ethics 3: Ethics in Data Processing | 1 |
| CET802 DS1: Descriptive Analytics | 1 |
| CET803 DS2: Predictive Analytics | 1 |
| CET804 DS3: Pattern Recognition | 1 |
| CET806 Application 1: Introduction to Affective AI | 1 |
| CET808 Application 3: Introduction to Cloud AI | 1 |
FlexiMasters in Artificial Intelligence and AI Ethics
| COURSE TITLE | ACADEMIC UNIT |
| CET787 Foundations of Computation Thinking and Programming | 1 |
| CET788 AI 1:AI Foundation | 1 |
| CET789 AI 2: Reinforcement Learning | 1 |
| CET790 AI 3: Computational Game Theory | 1 |
| CET791 ML1: Supervised learning: Bayesian decision theory and classifiers | 1 |
| CET792 ML2: Supervised learning: Non-probabilistic classifiers | 1 |
| CET793 ML3: Unsupervised learning | 1 |
| CET794 AI Ethics 1: Foundations of AI Ethics | 1 |
| CET795 AI Ethics 2: AI Ethic Standardization | 1 |
| CET797 Body of Knowledge (BoK) for AI Ethics and Governance | 1 |
| CET798 AI Ethics Governance Framework for Organisations | 1 |
| CET799 Business Liability and Ethics in AI Usage | 1 |
| CET800 AI Ethics 3: Ethics in Data Processing | 1 |
| CET801 Governance for AI Explainability | 1 |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Data Science and Artificial Intelligence, Graduate Certificate in Artificial Intelligence and AI Ethics (total 9AUs), and FlexiMasters in Data Science and Artificial Intelligence and FlexiMasters in Artificial Intelligence and AI Ethics (total 15AUs).
- SkillsFuture Credit approved.
