Data Analytics and Business Intelligence PG (8697.4)
Level: | Postgraduate Level |
---|---|
Credit Points: | 3 |
HECS Bands: | Band 1 2021 (Commenced After 1 Jan 2021) Band 1 2021 (Commenced Before 1 Jan 2021) Band 2 2013-2020 (Expires 31 Dec 2020) |
Faculty: | Faculty of Science and Technology |
Discipline: | Academic Program Area - Technology |
Availability
-
UC - Canberra, Bruce
Year Teaching Period Convener Mode of Delivery 2021 Semester 2 DR Yibe ALEM (Ph: +61 2 62068309 ) ON-CAMPUS
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Unit Outlines
To view your Unit Outline, click View to log in to MyUC and access this information, or visit your unit's online teaching site.
- Semester 2, 2020, ON-CAMPUS, BRUCE (195585) - View
- Semester 1, 2020, ON-CAMPUS, BRUCE (193957) - View
- Semester 2, 2019, ON-CAMPUS, BRUCE (185310) - View
- Winter Term, 2019, ON-CAMPUS, BRUCE (185605) - View
- Semester 2, 2018, ON-CAMPUS, BRUCE (182358) - View
- Winter Term, 2018, ON-CAMPUS, BRUCE (182355) - View
- Winter Term, 2017, ON-CAMPUS, BRUCE (166195) - View
- Winter Term, 2016, ON-CAMPUS, BRUCE (152412) - View
- Winter Term, 2015, ON-CAMPUS, BRUCE (141152) - View
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Syllabus
This unit introduces students to the tools and techniques of data analytics with application to business intelligence. Students will be introduced to the main tools of data analytics, both descriptive and predictive. Case studies will provide the links to intelligence that businesses, in the broadest sense of the term, can use. The unit is designed to be of interest to students in a range of disciplines including health, education, sport and management.This unit is co-taught with unit 8696 Data Analytics and Business Intelligence.
Learning Outcomes
On successful completion of this unit, students will be able to:
1. Source and access data from a variety of databases;
2. Select and apply appropriate tools for data visualization;
3. Select and apply descriptive data analytics methods;
4. Select and apply predictive data analytics methods;
5. Fit statistical models; and
6. Use the results to produce business intelligence in a variety of settings.
Assessment Items
Contact Hours
3 hours per week.
Prerequisites
6554 Introduction to Statistics G or a similar unit.
Corequisites
None.
Assumed Knowledge
None.
Incompatible Units
8696 Data Analytics and Business Intelligence.
Equivalent Units
None.
Referenced Courses
- 179JA Graduate Certificate in Statistics
- 844AA Graduate Diploma in Business Informatics
- 843AA Graduate Diploma in Information Technology
- 839AA Graduate Diploma in Statistics
- 309JA Master of Business Informatics
- 845AA Master of Business Informatics
- ITM001 Master of Data Science
- 354JA Master of Engineering
- 846AA Master of Information Technology
- 973AA Master of Information Technology and Systems
- 900AA Master of Technology
- 862AA Professional Doctorate in Information Sciences (Research)