Highlights about course

Program Level

Bachelor

Duration

3 Years

Tuition Fees

RM48,160

Intake

March, September

Harness the power of data for a career at the forefront of data-driven decision making and forecasting. Get hands-on with the tools used to manage big data sets and gain insight into how data is used to solve problems and even spot them before they arise. Make yourself an indispensable member of any business with roles in government, marketing, finance, healthcare and more.

Course details

Course objectives

Students who successfully complete this course will be able to:

  • Apply a broad and coherent knowledge of data science in diverse contexts and domains using critical thinking and judgment
  • Employ appropriate methods and contemporary tools used in different domains of data science
  • Communicate proficiently to a variety of audiences, function as an effective member or leader of a team, and use the contemporary tools and practices of project management within project work
  • Demonstrate professionalism, integrity, ethical conduct, professional accountability and an awareness of professional practice in a global context
  • Utilise data analysis and decision-making methodologies to glean insights into industry relevant problems for the benefit of organisations
  • Reflect on personal performance, learning, and self-management processes as a means of continued professional development.

Course structure

For the completion of Bachelor of Data Science, students are required to complete a total of 24 units (300 credit points) consisting of:

  • 8 units in core studies (100 credit points)
  • 8 units in major study (100 credit points)
  • 8 units of other studies (100 credit points) comprising a co-major, minor, advanced minor, internship or electives

Units of study

Core Units

8 units (100 credit points)

Units Unit codes Credit points
Introduction to Programming COS10009 12.5
Web Technology Project COS10026 12.5
Networks and Switching TNE10006 12.5
Computer Systems COS10004 12.5
Object Oriented Programming COS20007 12.5
Technology in an Indigenous Context Project COS10025 12.5
Computing Technology Project A* COS40005 12.5
Computing Technology Project B* COS40006 12.5

Major: Data Science

8 units (100 credit points)

Units Unit codes Credit points
Cloud Computing Architecture COS20019 12.5
Database Design Project COS20031 12.5
Computing Technology Innovation Project* COS30049 12.5
Software Architecture and Design* SWE30003 12.5
Data Science Principles COS10022 12.5
Big Data Architecture and Application* COS20028 12.5
Data Visualisation* COS30045 12.5
Software Deployment and Evolution SWE40006 12.5

Electives/Minor/Second Major

8 units in other studies (100 credit points)

 

Fees & scholarships

Fee*

Malaysian students
RM38,000 (annual)
International students
RM48,160 (annual)

 

* The indicative course fees shown here applies to students studying on-campus in Malaysia for the relevant year only. They are based on a standard study load per year. However, please note that fees are assessed according to a student’s study load in each semester, and variation to study load will result in an adjustment to tuition fees. All fees are subject to annual review and may be adjusted.

Scholarships

At Swinburne scholarships are about providing opportunity, promoting equity and recognising excellence and achievement. Scholarships are available for both commencing and current students.

Find your scholarship

Entry requirements

Entry Requirements

Assess your eligibility for entry to Swinburne Sarawak.

English Requirements

Find out more about English language requirements.

Application process

Apply for this course by following the step-by-step process from the links below.

  • Learn more on the application process

Career opportunities

Bachelor of Data Science graduates will have extensive skills in data science, particularly relating to medium- and large-scale projects. They will have developed experience in working in team projects and will have well-developed orang and written communication skills, with potential career options as data scientist, data engineer, machine learning engineer, data warehouse architect, and data analyst.

About University

Swinburne University of Technology Malaysia

Malaysia

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