Graduate Certificate of Data Science
Course handbook
General Information
Overview
The Graduate Certificate of Data Science is for students who want to expand their knowledge of computer science and data analytics. This course will build on a student's undergraduate qualifications or relevant industry experience, with an emphasis on managing, interpreting and visualising data sets. Students will study a project-based learning unit and graduate ready to work in data-driven decision-making roles.
Study structure
Successful completion of the Graduate Certificate of Data Science requires students to complete units of study to the value of 100 credit points. All units of study are valued at 12.5 credit points unless otherwise stated.
Full-time study: 100 credit points/eight standard units of study per year
Part-time study: 50 credit points/four standard units of study per year
One credit point is equivalent to one hour of study per week per semester (including contact hours and private study)
See the course planner for an example degree structure.
Full-time study: 100 credit points/eight standard units of study per year
One credit point is equivalent to one hour of study per week per semester (including contact hours and private study)
See the course planner for an example degree structure.
Units of study | Unit code |
---|---|
Core units | |
Creating Web Applications
Core unit, 12.5 credit points |
COS60004 |
Introduction to Data Science
Core unit, 12.5 credit points |
COS60008 |
Data Management for the Big Data Age
Core unit, 12.5 credit points |
COS60009 |
Technology Inquiry Project
Core unit, 12.5 credit points |
COS60010 |
Technology Design Project
Core unit, 12.5 credit points |
COS60011 |
User-Centred Design
Core unit, 12.5 credit points |
COS70004 |
Cloud Computing Architecture
Core unit, 12.5 credit points |
COS80001 |
Data Visualisation
Core unit, 12.5 credit points |
COS80025 |
Aims and objectives
On successful completion of this course students will be able to:
- Apply a coherent understanding of the concepts and practices within the field of Data Science as an effective member of diverse teams in a professional context
- Critically analyse various Data Science scenarios, evaluate the existing knowledge base, and propose and justify effective and/or innovative solutions, including the choice of appropriate technology
- Engage with solutions for practical applications with personal discipline, critical thinking, and scholarship skills
- Communicate information proficiently to technical and non-technical audiences, including industry practitioners
Career opportunities
This postgraduate course will build on a student's cognate undergraduate qualifications or relevant industry experience by developing skills in relation to managing, interpreting, visualising and deriving knowledge from small to medium-sized data sets, allowing them to take on a variety or roles in data-driven decision making.
Maximum Academic Credit
The maximum level of credit that can be granted for the Graduate Certificate of Data Science is 50 credit points (normally four units).
Volume of Learning
The Graduate Certificate of Data Science consists of 100 credit points. A standard annual full-time load comprises 100 credit points and a part-time load comprises 50 credit points. The volume of learning of the Graduate Certificate of Data Science is typically one year.
Admission criteria
Information about Swinburne's general admission criteria can be found at Admissions at Swinburne - Higher Education webpage.
Interested in the Graduate Certificate of Data Science?
From state-of-the-art facilities to opportunities to engage with industry – this course is designed with your future in mind. Let's get started.