Courses & Units
Artificial Intelligence and Big Data Applications for Business BEA319
Introduction
AI and Big Data are popular buzzwords that are generating significant interest by businesses in today’s digital world. Business managers are increasingly investing in these technologies with the hope that automation and access to more data can lead to cost savings, create new business opportunities and sustain competitive advantages. This unit seeks to demystify AI and Big data for business managers and to engender critical reflection on the unintended consequences and ethical issues for businesses associated with the introduction of these emerging technologies.
Summary
| Unit name | Artificial Intelligence and Big Data Applications for Business |
|---|---|
| Unit code | BEA319 |
| Credit points | 12.5 |
| College/School | College of Business & Economics Tasmanian School of Business and Economics |
| Discipline | Finance |
| Coordinator | Doctor Glenn Finau |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
Availability
This unit is currently unavailable.
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Describe the local and global impact of AI and Big data on individuals, organisations, and society
- Appraise AI technologies and cloud computing services for businesses.
- Solve complex business problems using artificial intelligence and big data technologies.
- Critically evaluate the ethical issues and risks associated with AI and big data for businesses.
- Recommend appropriate approaches for the tactical implementation of AI and Big Data for businesses.
Fee Information
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| not applicable |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Teaching
| Teaching Pattern | Pre-recorded Blended Lecture (online), Up to 1.5 hours (3-5 short lectures of maximum 20 minutes each), weekly. Blended Workshop (face to face and via zoom) for 180 minutes. 4 blocks of 3 hour workshops. |
|---|---|
| Assessment | Predictive analytics (30%)|Organisation evaluation of AI and Big Data (35%)|Take home exam (35%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
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