GD111 - Graduate Diploma in Analytics

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Plan: GD111P12 - Graduate Diploma in Analytics
Campus: City Campus

Learning outcomes

Program Learning Outcomes Statement

The program has a student-focused approach that aims at developing superior skill levels in the use of statistics and operations research in solving real world problems arising in industry, research and the business environments. This is achieved by the use of contemporary statistical software accompanied by an in-depth understanding of the statistical processes involved and how these processes impact in a variety of environments. By completing this program, you will be particularly knowledgeable, creative and critical in your approach to interpreting and analysing data. You will also be equipped with the ability to apply knowledge acquired to solve a wide range of real world problems.

Please note that the following list of PLOs applies to MC242 Master of Analytics. Students exiting MC242 with the Graduate Diploma award will have developed knowldge, skills and their application in areas identified below but not at an AQF 9 program level. Importantly they will not have completed a significant research capstone experience. 

The following are the key learning outcomes developed in the MC242 program which will make you, as a graduate, relevant to current industry and business requirements:

Personal and professional awareness

  • the ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
  • the ability to reflect on experience and improve your own future practice
  • the ability to apply the principles of lifelong learning to any new challenge.

Knowledge and technical competence

  • an understanding of appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.

Problem-solving

  • the ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
  • an understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.

Communication

  • the ability to effectively communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral), and to tailor the style and means of communication to different audiences.  Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.

Information literacy

  • the ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.
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