The OBE is a method of curriculum design, teaching and learning where it emphasises on the outcome of the learning process. For instance, what the current students have gained from the teaching and learning process, and for the graduated students –in a few years after they have left the university.
The focus of OBE lies on the professional attributes of the graduates, where the motivation is to fulfil the enduring demands of the country and the global market.
Introduction and Programme Educational Objective
This programme was introduced in the 2017/18 academic year to meet the ever-growing demand of professional practitioners in the field of Big Data Analytics.
The goal of this programme is to produce workforce/professional practioners in the field of Big Data Analytics who are capable of making right decisions based on the availability of comprehensive data. Therefore, the educational objective of this programme is to produce computing practitioners who:
[PEO1] have advanced knowledge in the field of Data science and Analytics capable of adopting best methodologies, tools and techniques to provide innovative solutions across various sectors.
[PEO2] have leadership skills, and are able to communicate as well as interact effectively with diverse stakeholders.
[PEO3] have positive attitudes, lifelong-learning capabilities and entrepreneurial mind-set for successful career.
[PEO4] uphold and defend ethical and professional practices in maintaining self and professional integrity.
Programme Learning Outcomes
At the end of this programme, the students will be able to:
PLO1 |
C1 - Knowledge & Understanding |
integrate advanced knowledge related to current practices and research issues in Data Science and Analytics; |
PLO2 |
C3A - Practical Skills |
conduct standard approaches and apply practical skills, tools or investigative techniques which are at the forefront of Data Science and Analytics; |
PLO3 |
C2 - Cognitive Skills |
recommend innovative solutions and ideas that is at the forefront of developments in Data Science and Analytics; |
PLO4 |
C3C - Communication Skills |
communicate clearly the knowledge, skills, ideas, critique and rationale using appropriate methods to peers, experts and nonexperts; |
PLO5 |
C3B - Interpersonal Skills |
work together and interact effectively with different people in learning and working communities and other groups and networks; |
PLO6 |
C5 - Ethics & Professionalism |
uphold professional and ethical practices in conducting research and delivering services related to the field of Data Science and Analytics; |
PLO7 |
C4A - Personal Skills |
exhibit capabilities to extend knowledge through life-long learning related to Data Science and Analytics; |
PLO8 |
C4B - Entrepreneurship Skill |
exhibit entrepreneurial mind-set related to Data Science and Analytics; |
PLO9 |
C3F - Leadership, Autonomy & Responsibility |
demonstrate leadership, autonomy and responsibility in delivering services related to Data Science and Analytics; |
PLO10 |
C3D - Digital Skill |
competently use and adapt a wide range of suitable digital technologies and appropriate software to enhance professional practice in Data Science and Analytics; and |
PLO11 |
C3E - Numeracy Skill |
utilise numerical skills to acquire, interpret and extend knowledge in Data Science and Analytics. |
The following table provides the matrix for programme learning outcomes of this programme.
No. |
Course Code/Unit |
Course Title |
Programme Learning Outcomes |
||||||||||
Knowledge & Understanding |
Practical Skill |
Cognitive Skill |
Communication Skill |
Interpersonal Skill |
Ethics & Professionalism |
Personal Skill |
Entrepreneurship Skill |
Leadership, Autonomy & Responsibility |
Digital Skill |
Numeracy Skill |
|||
CORE COURSES |
|
|
|||||||||||
1. |
CDS501/4 |
Principles and Practices of Data Science and Analytics |
√ |
√ |
√ |
√ | |||||||
2. |
CDS502/4 |
Big Data Storage and Management |
√ |
√ |
√ |
√ |
|||||||
3. |
CDS503/4 |
Machine Learning |
√ |
√ |
√ |
√ |
|||||||
4. |
CDS504/4 |
Enabling Technologies and Infrastructures for Big Data |
√ |
√ |
√ |
||||||||
5. |
CDS505/4 |
Data Visualisation and Visual Analytics |
√ |
√ |
√ |
√ |
|||||||
6. |
CDS506/4 |
Research, Consultancy and Professional Skills |
√ |
√ |
√ |
√ |
√ |
√ |
|||||
7. |
CDS590/8 |
Consultancy Project and Practicum |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
||||
ELECTIVE COURSES |
|
|
|||||||||||
8. |
CDS511/4 |
Consumer Behavioural and Social Media Analytics |
√ |
√ |
√ |
√ |
|||||||
9. |
CDS512/4 |
Business Intelligence and Decision Analytics |
√ |
√ |
√ |
√ |
|||||||
10. |
CDS513/4 |
Predictive Business Analysis |
√ |
√ |
√ |
√ |
√ |
||||||
11. |
CDS521/4 |
Multimodal Information Retrieval |
√ |
√ |
√ |
||||||||
12. |
CDS522/4 |
Text and Speech Analytics |
√ |
√ |
√ |
||||||||
13. |
CDS523/4 |
Forensic Analytics and Digital Investigations |
√ |
√ |
√ |
√ |