Business Analytics and Artificial Intelligence
Overview
This unit aims to develop and enhance students' conceptual and practical understanding of data analytics and artificial intelligence in the contemporary business context. Students will have an opportunity to immerse themselves in problem-solving activities requiring lateral and critical thinking by exploring structured and unstructured data, considering and applying the appropriate analytic and artificial intelligence techniques using a software programming environment for statistical computing (such as R) and visualisation tools and approaching organisational problems through data-driven decision-making processes. Further, students will learn fundamental concepts, key techniques and popular tools in artificial intelligence and how it is applied in business and industry.
Requisites
Rule
200 credit points
Assumed Knowledge
Basic understanding of computer programming
27-October-2024
01-June-2025
02-November-2025
Learning outcomes
Students who successfully complete this unit will be able to:
- Demonstrate an understanding of the roles of business analytics and artificial intelligence in various organisational contexts
- Synthesise and develop appropriate business solution scenarios using appropriate machine learning, analytics and visualisation techniques
- Analyse business problems and define the data requirements and business rules associated with the data-driven and machine learning problem-solving approaches
- Demonstrate critical thinking and problem solving through statistical and machine learning computing and visualization
- Communicate effectively as a professional and function as an effective leader or member of a team
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| On-campus Class | 2.00 | 12 weeks | 24 |
| Online Directed Online Learning and Independent Learning | 1.00 | 12 weeks | 12 |
| Unspecified Activities Various | 9.50 | 12 weeks | 114 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Problem Solving | Individual | 20 - 30% | 3,4 |
| Project | Group | 30 - 50% | 1,2,3,4,5 |
| Project | Individual | 30 - 40% | 2,3,4 |
Content
- The role and value of business analytics and artificial intelligence in business operations and strategic planning.
- The difference between business rules and business data requirements.
- Artificial intelligent applications as sources of business data
- How Artificial Intelligence can support and enhance marketing analytics, financial analytics, sports analytics, geospatial analytics, security analytics, health analytics, Social Network Analysis (SNA).Â
- The use of Artificial Intelligence in data analysis visualisation, dashboard design, storyboardingÂ
- Predictive, prescriptive, sentiment analytics, geospatial analytics
- Fast data, data lake, social media data, open data
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.