Graduate Diploma in Data Science (Applied) [Online] (GDipDS (App))

Program Code

GDDSA

Academic Year

2023

Program Faculty

Faculty of Sciences, Engineering and Technology

Special Notes

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These Program Rules should be read in conjunction with the University's policies (http://www.adelaide.edu.au/policies).

Overview

The Graduate Diploma in Data Science (Applied) [online] is a fully online program suitable for students from a wide range of backgrounds and will provide the opportunity to build skill and expertise in the application of data science. Data Science is a rapidly evolving space with implications for the future of work and our daily lives.

Students will undertake a fixed study plan within the online program, moving through two course carousels that structure their learning to build on appropriate prerequisite knowledge. The first carousel provides foundational content in data science, including fundamental technical content, as well as an overview of data science as an organisational process. The second carousel, then extends this content further, providing deeper technical awareness of data science, as well as exploration of case studies of application, communication and visualisation from multiple disciplines.

The Graduate Diploma in Data Science (Applied) [online] is an AQF Level 8 qualification with a standard full-time duration of 1 year. However, this program is only offered  part-time for a duration of 1.3 years.
 

Conditions

Condition of Enrolment
Interruption of program: Students must apply for permission from the Faculty before taking a Leave of Absence. Any extension of the leave without approval will result in the loss of place in the program but an application may be made to be re-admitted to the program subject to the admission procedures in place at the time.

Academic Program Rules for Graduate Diploma in Data Science (Applied) [Online]

There shall be a Graduate Diploma in Data Science (Applied) [Online].

Qualification Requirements
Academic Program: 

To qualify for the degree of Graduate Diploma in Data Science (Applied) [online], the student must complete satisfactorily a program of study consisting of the following requirements with a combined total of not less than 24 units, comprising:

  1. Core courses to the value of 24 units
  2. Students entering from a cognate discipline, and therefore unable to take COMP SCI 7210OL. Foundations of Computer Science – Python A and/or COMP SCI 7211OL. Foundations of Computer Science – Python B will be required to undertake the alternative course offerings. Students with permission to undertake alternative course offerings can contact the Student Success Team for further information.  
  3. Students without Stage 2 Mathematical Methods (or equivalent) are required to take MATHS 7203OL Applied Data Science and Mathematics in lieu of DATA 7202OL Applied Data Science. Students with permission to undertake alternative course offerings can contact the Student Success Team for further information.  
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Core Courses

To satisfy the requirements for Core Courses students must complete courses to the value of 24 units.

All of the following courses must be completed:

Subject / Catalogue Course Title Unit Value
COMP SCI 7210OL Foundations of Computer Science - Python A 3
COMP SCI 7211OL Foundations of Computer Science - Python B 3

or

Courses to the value of 6 units from the following:

Students entering from a cognate discipline, and therefore unable to take COMP SCI 7210OL Foundations of Computer Science – Python A and/or COMP SCI 7211OL Foundations of Computer Science – Python B will be required to undertake alternative course offerings.

and

Courses to the value of 3 units from the following:

Subject / Catalogue Course Title Unit Value
DATA 7202OL Applied Data Science 3
MATHS 7203OL Applied Data Science and Mathematics 3

and

All of the following courses must be completed:

Subject / Catalogue Course Title Unit Value
COMP SCI 7212OL Human and Ethical Factors in Computer Science 3
DATA 7201OL Data Taming, Modelling and Visualisation 3
DATA 7301OL Applications of Data Science 3
DATA 7302OL Real Data: Modern Methods for Finding Hidden Patterns 3
MATHS 7027OL Mathematical Foundations of Data Science 3
Published on: 30 November, 2022 | 09:49:03