Outcome Based Education

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

√ 

√ 

√ 

   

√ 

         

School of Computer Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia
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