Programme Structure

Credit requirements: 44 units


(i)    Core Courses: 24 units (Code: T)     


CDS501/4 – Principles and Practices of Data Science and Analytics


CDS502/4 – Big Data Storage and Management


CDS503/4 – Machine Learning


CDS504/4 – Enabling Technologies and Infrastructures for Data Science


CDS505/4 – Data Visualisation and Visual Analytics


CDS506/4 – Research, Consultancy and Professional Skills


(ii)   Elective Courses: 12 Units (Code: E)

        Choose any three (3) courses from the table below:


Business Analytics


CDS511/4  –   Consumer Behavioural and Social Media Analytics


CDS512/4  –   Business Intelligence and Decision Analytics


CDS513/4  –   Predictive Business Analytics

Multimodal Analytics


CDS521/4  –    Multimodal Information Retrieval


CDS522/4  –    Text and Speech Analytics


CDS523/4  –    Forensic Analytics and Digital Investigations


 (iii)  Project (Core): 8 units (Code: T)

         CDS590 – Consultancy Project and Practicum

This experiential work-based learning course prepares students to be a data scientist/analytics consultant by enhancing the students’ knowledge and skills in research, planning and implementation of a consultancy project in the field of data science/analytics, which can be applied to real-life situation.  Students are required to complete the practicum at their respective workplace or their chosen/assigned organisation. Students work under the supervision of a lecturer and an industry mentor. The students are required to solve a real-world problem or tap opportunities related to data science and analytics during their practicum. The prerequisite of this course is CDS506 which must be taken in the preceding semester. The students are required to secure practicum placement together with project proposal during CDS506.