ANA504 – Predictive Analytics and Forecasting

Unit code & Title	ANA504 - Predictive Analytics and Forecasting
Pre-requisite	Not Applicable
Delivery modes	On-campus; Online;
Credit points	10
Study commitment	Average of 150 hours of teaching, learning and assessment over the trimester.
Scheduled learning (On-campus)	2 × 3 hours on-campus seminar and tutorial weekly (for block mode)
Scheduled learning (AIA Online)	Recorded contents + 2 × 3 hour online seminar and tutorial weekly
Learning Outcomes	ULO1: Discuss the fundamental concepts behind predictive analytics and forecasting. ULO2: Explore and apply the predictive analytics and forecasting methods. ULO3: Explore and apply advanced engineering techniques using machine learning and deep learning, and global models – including RNNs, transformers, and N-BEATS; and using combined multiple forecast models with assembling and stacking. ULO4: Evaluate and validate forecasts using best practices and statistical metrics. ULO5: Apply predictive analytics and present forecasting results using the above methods and models. ULO6: Working collaboratively with team members on a predictive analytics project.

Overview

Predictive Analytics & Forecasting covers the fundamental concepts underlying business intelligence systems, data analytics and methods, and the supporting ecosystems.

Students learn the application of analytics across multiple industries using the different techniques including descriptive analytics, data visualisation in business reporting, predictive analytics, text analytics, social media analytics, and prescriptive analytics such as linear programming, simulation and optimization modelling.

The unit also extends to the data foundation for data warehousing and data lakes application and explore big data ecosystems and the emerging trends business analytics including location analytics, Internet of Things, cloud-based analytics, and privacy concerns.

The unit is aligned with the following course learning outcome (CLO):

• CLO5: Develop specialised skills and knowledge in a chosen area of business analytics through completion of specialisation units and a Research Project.
• CLO6: Utilise business intelligence tools and techniques to generate insights from data and create meaningful reports for decision-making purposes.

Unit Fee Information

Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study and their study discipline, and your study load.

Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.

For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit Current student page

Important Dates

Refer to Academic Calendar