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Introduction
Computer / software engineers are involved in effective and efficient building of knowledge-based agent systems, including software for intelligent embedded systems and intelligent information systems. This course teaches general awareness of theory, knowledge, and practice in all phases of the development of knowledge-based systems and knowledge representation techniques, which are necessary for those who want to enter the field of artificial intelligence. This course provides a comprehensive introduction to artificial intelligence, emphasizing fundamental topics.
- Graduate Certificate in Artificial Intelligence and AI Ethics
- Graduate Certificate in Data Science and Artificial Intelligence
- Graduate Certificate in Artificial Intelligence and AI Plus
- FlexiMasters in Artificial Intelligence and AI Ethics
- FlexiMasters in Data Science and Artificial Intelligence
- FlexiMasters in Artificial Intelligence and AI Plus
Download Learning Pathway e-Guide
At the end of the course, learners are able to:
1. Explain what Artificial Intelligence is about and appreciate its relevance to Computer Science and importance for IT and society;
2. Describe the human cognitive organisation in problem solving and appreciate the ethics involved in the application of AI techniques and;
3. Formulate a problem, evaluate its complexity and apply the appropriate state space search algorithms to solve it.
1. Foundations of AI, the history of AI, and recent progress
2. Agent paradigm, agent tasks and environments
3. Problem formulation, state space representation
4. Uninformed search (breadth-first, depth-first, IDA, uniform-cost)
5. Informed search (best-first, A*), heuristics functions
6. Constraint satisfaction problems
7. Adversarial search (Minimax) for game playing
For learner who wish to acquire more knowledge in applying AI practices in organizations and, to understand and help societies to solve problems brought about by the impact of AI.
Standard Course Fee: S$1,962
SSG Funding Support | Course fee | Course fee payable after SSG funding, if eligible under various schemes | |
BEFORE funding & GST | AFTER funding & 9% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | S$1,800 | S$588.60 | |
Enhanced Training Support for SMEs (ETSS) | S$228.60 | ||
SCs aged ≥ 40 years old | |||
- Standard course fee is inclusive of GST.
- NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Artificial Intelligence and AI Ethics
| COURSE TITLE | ACADEMIC UNIT |
| CET787 Foundations of Computation Thinking and Programming | 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 |
| CET807 Application 2: Introduction to Computer Vision | 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 |
Data Science and Artificial Intelligence
| COURSE TITLE | ACADEMIC UNIT |
| CET787 Foundations of Computation Thinking and Programming | 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 |
| CET802 DS1: Descriptive Analytics | 1 |
| CET803 DS2: Predictive Analytics | 1 |
| CET804 DS3: Pattern Recognition | 1 |
| CET805 AI Ethics 3: Ethics in Data Processing | 1 |
| CET806 Application 1: Introduction to Affective AI | 1 |
| CET807 Application 2: Introduction to Computer Vision | 1 |
| CET808 Application 3: Introduction to Cloud AI | 1 |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Artificial Intelligence and AI Ethics, Graduate Certificate in Data Science and Artificial Intelligence (total 9AUs), FlexiMasters in Artificial Intelligence and FlexiMasters in Data Science and Artificial Intelligence (total 15AUs).
- SkillsFuture Credit approved.
