CET793 ML3: Unsupervised learning

Course Provider

School of Computer Science and Engineering (SCSE)

Certification

FlexiMasters

Academic Unit

1

Introduction

The course provides an overview of unsupervised learning techniques, such as K-means, PCA, and density estimation.

This course is part of:

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



By the end of the course, learners are able to:

1. Understanding the principles of unsupervised learning methods and;

2. Knowing how to use sciki-learn to implement such methods.

K-means clustering algorithm, PCA algorithm, density estimation methods. 

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
SkillsFuture Mid-career Enhanced Subsidy (MCES)
(Up to 90% funding)

  • Standard course fee is inclusive of GST.
  • NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.

 

Read more about funding

Artificial Intelligence and AI Ethics

COURSE TITLEACADEMIC UNIT
CET787 Foundations of Computation Thinking and Programming 1
CET788 AI 1:AI Foundation1
CET789 AI 2: Reinforcement Learning1
CET790 AI 3: Computational Game Theory1
CET791 ML1: Supervised learning: Bayesian decision theory and classifiers1
CET792 ML2: Supervised learning: Non-probabilistic classifiers1
CET794 AI Ethics 1: Foundations of AI Ethics1
CET795 AI Ethics 2: AI Ethic Standardization1
CET807 Application 2: Introduction to Computer Vision1
CET797 Body of Knowledge (BoK) for AI Ethics and Governance1
CET798 AI Ethics Governance Framework for Organisations1
CET799 Business Liability and Ethics in AI Usage1
CET800 AI Ethics 3: Ethics in Data Processing1
CET801 Governance for AI Explainability1

 

Data Science and Artificial Intelligence

COURSE TITLEACADEMIC UNIT
CET787 Foundations of Computation Thinking and Programming1
CET788 AI 1:AI Foundation1
CET789 AI 2: Reinforcement Learning1
CET790 AI 3: Computational Game Theory1
CET791 ML1: Supervised learning: Bayesian decision theory and classifiers1
CET792 ML2: Supervised learning: Non-probabilistic classifiers1
CET794 AI Ethics 1: Foundations of AI Ethics1
CET795 AI Ethics 2: AI Ethic Standardization
1
CET802 DS1: Descriptive Analytics
1
CET803 DS2: Predictive Analytics
1
CET804 DS3: Pattern Recognition1
CET805 AI Ethics 3: Ethics in Data Processing1
CET806 Application 1: Introduction to Affective AI1
CET807 Application 2: Introduction to Computer Vision 1
CET808 Application 3: Introduction to Cloud AI1

 

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.