University of Technology Sydney

C11274v3 Graduate Certificate in Data Science and Innovation

Award(s): Graduate Certificate in Data Science and Innovation (GradCertDataScInn)
CRICOS code: 084266A
Commonwealth supported place?: No
Load credit points: 24
Course EFTSL: 0.5
Location: City campus

Notes

No further Commonwealth-supported places available for 2025.


Overview
Career options
Course intended learning outcomes
Admission requirements
Inherent requirements
Course duration and attendance
Course structure
Course completion requirements
Other information

Overview

The Graduate Certificate in Data Science and Innovation is designed for students to gain data science skills in a fast-paced mode. It has a flexible and comprehensive course structure with a group of fundamental and advanced subjects. This allows people with different backgrounds and learning objectives to take the course either as a fast-track pathway into the data science industry, or to develop specialised skills to further enhance their data science career.

Taking a transdisciplinary approach, the course integrates fundamental theories with industry experiences, real-world projects and self-directed study, equipping graduates with an understanding of the potential of analytics to transform practice. The course is delivered in a range of modes, including contemporary online and face-to-face learning experiences in UTS's leading-edge facilities.

Upon successful completion of the graduate certificate, students can also choose to progress to the Graduate Diploma in Data Science and Innovation (C60124) or Master of Data Science and Innovation (C04372), a world-leading program of study in analytics and data science.

The dramatic growth of data in every conceivable industry, from oceanography to market research, presents another major driving force in generating unprecedented global demand for data science skills.

Career options

The course prepares students to participate in a variety of emerging careers with the growth of data science. While other offerings also provide the basis for these careers, this unique transdisciplinary course is the first of its kind in Australia where creativity and innovation are integral components, producing industry-ready graduates with strong technical, creative thinking and data ethics skills.

Course intended learning outcomes

1.1 Identify and represent the human and technical elements and processes within complex systems and organise them within frameworks of relationships
1.2 Explore and test models and generalisations for describing the behaviour of sociotechnical systems and selecting data sources, taking into account the needs and values of different contexts and stakeholders
2.1 Critique contemporary trends and theoretical frameworks in data science for relevance to one's own practice
2.2 Explore, analyse, manipulate, interpret and visualise data using data science techniques, software and technologies to make sense of data rich environments
3.1 Explore, interrogate, generate, apply, test and evaluate problem-solving strategies to extract economic, business, social, strategic or other value from data
4.1 Collaborate to develop and refine multimodal communication skills needed to successfully work in data science teams
5.1 Engage in active, reflective practice that supports flexible navigation of assumptions, alternatives and uncertainty in professional data science contexts
5.2 Take a leadership role in promoting positive change in data science contexts, recognising individual, organisational and community issues, including indigenous worldviews and cultures.

Admission requirements

To be eligible for admission to this course, applicants must meet the following criteria.

Applicants must have one of the following:

  • Completed Australian bachelor's degree or higher qualification, or overseas equivalent, in any discipline with a minimum GPA of 4/7

OR

  • Completed Australian bachelor's degree or higher qualification, or overseas equivalent, in any discipline AND A minimum of 2 years full-time, or equivalent part-time, professional experience in a relevant professional occupation (listed below)

OR

  • Completed Australian bachelor's degree or higher qualification, or overseas equivalent, in a relevant discipline (listed below)

Relevant disciplines:

Natural and Physical Sciences, Information Technology, Engineering and related technologies, Accounting, Business and Management, Sales and Marketing, Banking, Finance and related fields, Economics and Econometrics

Relevant professional occupations (ANZCO classification):

2241 Mathematical Science Professionals, 2243 Economists, 2244 Intelligence and Policy Analysts, 225112 Market Research Analyst, 225115 Digital Marketing Analyst, 26 ICT Professionals

Supporting documentation to be submitted with the application

For applicants who need to demonstrate work experience:

  • Curriculum Vitae AND Statement of service in one of the following formats:
    • A 'Statement of Service' provided by the employer
    • A completed 'UTS statement of service’ signed by the employer
    • A statutory declaration confirming work experience (for Australian Residents only)
    • An official letter from the applicant’s accountant or solicitor on their company letterhead confirming the applicant’s work experience or engagement with the business, duration of operations, and the nature of the business
    • A business certificate of registration in original language and English (e.g. provision of ASIC documentation or ABN or similar documentation for Australian Businesses)

The English proficiency requirement for international students or local applicants with international qualifications is: IELTS Academic: 6.5 overall with a writing score of 6.0; or TOEFL iBT: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64 with a writing score of 50; or C1A/C2P: 176-184 with a writing score of 169.

Eligibility for admission does not guarantee offer of a place.

International students

Visa requirement: To obtain a student visa to study in Australia, international students must enrol full time and on campus. Australian student visa regulations also require international students studying on student visas to complete the course within the standard full-time duration. Students can extend their courses only in exceptional circumstances.

Inherent requirements

Inherent requirements are academic and non-academic requirements that are essential to the successful completion of a course. For more information about inherent requirements and where prospective and current students can get assistance and advice regarding these, see the UTS Inherent requirements page.

Prospective and current students should carefully read the Inherent Requirements Statement below and consider whether they might experience challenges in successfully completing this course.

UTS will make reasonable adjustments to teaching and learning, assessment, professional experiences, course related work experience and other course activities to facilitate maximum participation by students with disabilities, carer responsibilities, and religious or cultural obligations in their courses.

For course specific information see the TD School Inherent (Essential) Requirements Statement.

Course duration and attendance

Students generally complete the required credit points in six months of full-time or one year of part-time study.

Course structure

Students must complete 24 credit points in total.

Course completion requirements

STM91480 Data Science Core Subjects 24cp
Total 24cp

Other information

For further information, contact the UTS Student Centre:

telephone 1300 ask UTS (1300 275 887)
or +61 2 9514 1222
Ask UTS