University of Technology Sydney

C11274v2 Graduate Certificate in Data Science and Innovation

Award(s): Graduate Certificate in Data Science and Innovation (GradCertDataScInn)
CRICOS code: 084266A
Commonwealth supported place?: Yes
Load credit points: 24
Course EFTSL: 0.5
Location: City campus

Overview
Career options
Course intended learning outcomes
Admission 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

Applicants must have completed a UTS recognised bachelor's degree, or an equivalent or higher qualification, or submitted other evidence of general and professional qualifications that demonstrates potential to pursue graduate studies.

The qualification used for application for admission must have been completed with a GPA of at least 4.0 on a 7.00 GPA scale.

The English proficiency requirement for international students or local applicants with international qualifications is: Academic IELTS: 6.5 overall with a writing score of 6.0; or TOEFL: paper based: 550-583 overall with TWE of 4.5, internet based: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64; or CAE: 176-184.

Eligibility for admission does not guarantee offer of a place.

Local students

Local applicants who do not satisfy the minimum admission requirements listed above may be deemed eligible for admission if they:

  • have successful completed at least one microcredential subject in the Master of Data Science and Innovation course

OR

  • have sufficient data related knowledge and skills as indicated by at least two years of full time work experience. To support their application, they must provide:
    • a C.V. outlining work experience and education, as well as other relevant evidence and information, and
    • an official Statement of Service, from the employer, confirming the dates of employment, and a description of the position held within the organisation.

International students

International applicants who do not satisfy the minimum admission requirements listed above may be deemed eligible for admission if they have sufficient data related knowledge and skills as indicated by at least two-year of extensive full time, or equivalent part-time, work experience. To support their application, they must provide:

  • a C.V. outlining work experience and education, as well as other relevant evidence and information, and
  • an official Statement of Service, from the employer, confirming the dates of employment, and a description of the position held within the organisation.

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.

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