Graduate Certificate in Applied Data Science

includes:

Graduate Certificate in Applied Data Science
AQF level 8

Awards

Academic Senate has approved the following awards for conferral at graduation on a testamur:

Graduate Certificate in Applied Data Science GradCertAppDataScience

Availability

Graduate Certificate in Applied Data Science (2320AD)

Online - Bathurst

Availability is subject to change, please verify prior to enrolment.

Normal Course Duration

Course duration referenced below is the effective time taken to complete a course when studied full time (full time equivalent duration). At Charles Sturt the standard calendar refers to 32 points a session over a 2 session calendar year. The Actual Duration is the time taken to complete the course following the prescribed enrolment pattern. A course's actual duration can be affected by the session calendar (number of sessions undertaken per year) and/or mode (full time, part time or mixed) and credit packages which may have been granted upon admission. Therefore, depending on the prescribed enrolment pattern, mode, calendar utilised and credit awarded a course may take less time or more time to complete than the duration noted as full time equivalent years. Students are advised to consult the Enrolment Pattern to determine the actual duration of study.

Graduate Certificate in Applied Data Science

Full-time: 0.5 years (or part-time equivalent)

Admission Criteria

CSU Admission Policy

  • Bachelor degree from a recognised tertiary institution OR
  • Two years relevant work experience OR
  • Graduate Certificate in a related area.

Upon successful completion of the Graduate Certificate, students will be eligible for admission to the Master of Information Technology and receive credit for applicable subjects.

Credit

CSU Credit Policy

Standard Charles Sturt University Credit Policy applies: https://policy.csu.edu.au/document/view-current.php?id=120

Graduation Requirement

To graduate students must satisfactorily complete 32 points.

Course Structure

The course consists of one (1) Core subject and three (3) Restricted Elective subjects.

Core
ITC575 Foundations of Big Data Analytics

Restricted Electives
Choose 3 subjects from
ITC516 Data Mining and Visualisation for Business Intelligence
ITC556 Database Systems
ITC558 Programming Principles
ITC560 Internet of Things
ITC573 Data and Knowledge Engineering
ITC576 Artificial Intelligence and Machine Learning
STA427 Advanced Statistical Modelling
STA448 Multivariate Statistical Analysis
STA501 Scientific Data Analysis
STA508 Experimental Design and Analysis

Enrolment Pattern

There is no prescribed enrolment pattern. Enrolment patterns will depend upon students' choice of subjects, the prerequisite needs of subjects and the session of availability of subjects.

The information contained in the CSU Handbook was accurate at the date of publication: July 2022. The University reserves the right to vary the information at any time without notice.

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