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Introduction
This course aims to teach appropriate computing and programming techniques to learners, so that them can apply these techniques in the rest of the FlexiMasters.
- 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
At the end of the course, learners are able to:
1. Describe the processes and methods of Computational Thinking;
2. Write programs using the Python programming language and;
3. Solve standard algorithmic problems and perform standard numeric computations in Python.
This course is to teach learners how Computational Thinking is applied for solving problems through programming computers with Python. It is suitable for learners who have no experience in Python programming, and for those who want to learn the good practices used in writing programs.
For learner who wish to acquire more knowledge in applying ethical AI practices in organizations and, to understand and help societies to solve problems brought about by the impact of AI.
Standard Course Fee: S$1,944
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.
Artificial Intelligence and AI Ethics
| COURSE TITLE | ACADEMIC UNIT |
| 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 |
| 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 |
| 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 |
| 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 |
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).
- SSG funded and SkillsFuture Credit approved.
