Please note that some of the courses specified in the Graduate Diploma of Applied Data Analytics program will not be offered in intensive mode in 2024 and depending on enrolments may not be offered in intensive mode in 2025 either. Students will need to complete the approved alternative courses listed below on-campus, in standard semester schedules, that may include in-person examinations and tutorials. COMP8910 Data Mining (Intensive) replaced with COMP8410 COMP7240 Introduction to Database Concepts (intensive) replaced with COMP6240 COMP7230 Introduction to Programming for Data Scientists (intensive) replaced with COMP6730 The Graduate Diploma of Applied Data Analytics is a 1 year full-time (or equivalent part-time) degree that provides students with: Exposure to best practice in data analytics. Cutting edge courses in areas of relevance to data analytics practitioners. An opportunity to deepen knowledge in one of the three areas of computation, statistics, or social science. Professional development for practicing data analytics professionals. The opportunity to undertake research of professional relevance. The program is taught in semester mode, and for domestic students the program is also offered in intensive blended mode. Students studying in intensive blended mode are expected to be enrolled part-time. The intensive blended course delivery mode is designed to suit working students who take leave from work (or other commitments) to attend an intensive 1 week of full time learning on campus in the middle of the course, and study remotely for the rest of the course. The intensive blended course delivery mode comprises: 4 weeks of online study, 1 full time week of face to face learning on campus, followed by a further 4 weeks of online study.
Learning Outcomes
Apply computing, statistical, and social science principles to solve data analytics problems; Apply data analytics methods and techniques to decision making about policy, business and service delivery; Contribute as an effective member to the performance of a data analytics workplace; Demonstrate basic technical expertise in computing, statistics, and social science as relevant to data analytics. Be able to work to specification and according to a deadline, document tasks undertaken, and report outcomes to a third party. Be capable of independent learning with some ability to evaluate critically work undertake.
Career Options
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