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Course (2020)

Information on this page, including unit offerings, is from the 2020 academic year.

Graduate Diploma in Data Science (GradDipDataSci)

  • G1082GRADUATE DIPLOMA IN DATA SCIENCE

  • Course Outline
  • Course Structure
  • Fees
  • Course Plans
Title Graduate Diploma in Data Science (GradDipDataSci)
Course Code G1082
Study Level Graduate Diploma
Organisational Unit Information Technology, Mathematics and Statistics
Academic Contacts

Academic Chair: Dr Polychronis Koutsakis | Email: p.koutsakis@murdoch.edu.au | Tel: 9360 6475

Qualification Graduate Diploma in Data Science (GradDipDataSci)
Duration 1 year full-time or part-time equivalent
Availability Murdoch campus (internal)
Restriction All graduate courses are subject to restriction.
Description The Graduate Diploma in Data Science is designed to provide graduates in information technology related disciplines with knowledge and skills in the area of data science. The course emphasises data and business analysis as well as data resources management. This skill set is needed to work with what is commonly known as 'big data'.
Admission Requirements: Onshore course offerings Recognised Australian Computer Society (ACS) Bachelor's degree in IT (AQF Level 7);
OR recognised Bachelor's degree (AQF Level 7) plus an approved qualification in IT (AQF Level 8);
OR recognised Bachelor's degree (AQF Level 7) plus two years of relevant IT experience;
OR recognised Honours degree (AQF Level 8) plus relevant IT experience.
Recognition of relevant and current informal or non-formal learning may be used for entry requirements, and should be discussed with the Academic Chair.

Equivalent of an Academic IELTS overall score of 6.0 with no band less than 6.0.
Special Requirements The course is available by on-campus attendance only.
Course Learning Outcomes 1. Apply the tools and techniques of project management to support successful project completion.
2. Demonstrate a practical and theoretical understanding of advanced computational and statistical tools and methods for data-driven analysis and problem solving, including their limitations.
3. Choose, use, combine and evaluate techniques and technologies appropriate for different big data analysis tasks.
4. Demonstrate and articulate a critical understanding of the latest approaches, theories, and research activities in data science.
Employment Prospects Commerce, telecommunications, health, education, architecture, mining, engineering, law and government and non-government organisations
Main research areas machine learning, data mining
Online Study Murdoch units normally include an online component comprising materials, discussions, lecture recordings and assessment activities. All students, regardless of their location or mode of study, need to have access to and be able to use computing devices with browsing capability and a connection to the Internet via Broadband (Cable, ADSL or Mobile) or Wireless. The Internet connection should be readily available and allow large amounts of data to be streamed or downloaded (approximately 100MB per lecture recording). Students also need to be able to enter into online discussions and submit assignments online.
Further Study Students who successfully complete the Graduate Diploma may apply for admission to the Master of Information Technology.
Internet Access RequirementsMurdoch units normally include an online component comprising materials, discussions, lecture recordings and assessment activities. All students, regardless of their location or mode of study, need to have access to and be able to use computing devices with browsing capability and a connection to the Internet via Broadband (Cable, ADSL or Mobile) or Wireless. The Internet connection should be readily available and allow large amounts of data to be streamed or downloaded (approximately 100MB per lecture recording). Students also need to be able to enter into online discussions and submit assignments online.

Course Structure - 24 credit points

Core Units - 15 credit points

ICT521 IT Professional Practice - 3 points
MURDOCH: S1-internal, S2-internal

ICT515 Foundations of Data Science - 3 points
MURDOCH: S2-internal

ICT508 Information Technology Project Management - 3 points
MURDOCH: S1-internal, S2-internal

ICT619 Artificial Intelligence - 3 points
MURDOCH: S1-internal

ICT616 Data Resources Management - 3 points
MURDOCH: S1-internal, S2-internal

Specified Electives - 9 credit points

ICT612 Human Factors in Information Technology - 3 points
MURDOCH: S1-internal

ICT501 Business Analysis and Systems Development Approaches - 3 points
MURDOCH: S2-internal, S2-external

ICT505 Knowledge Management - 3 points
MURDOCH: S2-internal

ICT513 Data Analytics - 3 points
MURDOCH: S2-internal, S2-external

ICT546 Local Area Network Design and Implementation - 3 points
MURDOCH: S1-internal, S2-internal

ICT601 Business Analytics - 3 points
MURDOCH: S2-internal

ICT602 Advanced Data Analysis - 3 points
MURDOCH: S1-internal

ICT603 Wireless Data Communications - 3 points
MURDOCH: S2-internal

ICT622 Information Technology Strategy - 3 points
MURDOCH: S2-internal

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