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DSC3015 - Knowledge Graph and Cognitive Computing

Offering Academic Unit
Department of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Equivalent Course(s)
SDSC3015
Course Offering Term*:
Not offering in current academic year

* The offering term is subject to change without prior notice
 
Course Aims

This course aims to introduce knowledge graphs, knowledge representations and reasoning, semantic web and ontologies, knowledge graph and its applications, and the cognitive computing technologies. Students will learn how to represent knowledge and process knowledge using programming skills. Students will master the basic ideas of ontologies, semantic web, reasoning, and cognitive computing. Students will be able to construct ontologies for real-world problems. Students will use ontologies to represent the knowledge and perform various reasoning tasks on ontologies. Students will be familiar with latest applications of knowledge graphs in cognitive computing, and state-of-the-art cognitive systems.


Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 60%
Examination: 40%
Examination Duration: 2 hours
Min. Continuous Assessment Passing Requirement: 30%
Min. Examination Passing Requirement: 30%
 

Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components.

 
Detailed Course Information

DSC3015.pdf