Course Title: Advanced Business Analytics

Part A: Course Overview

Course Title: Advanced Business Analytics

Credit Points: 12.00


Course Coordinator: Dr Hamed Jahani

Course Coordinator Phone: +61 3 9925 0103

Course Coordinator Email: hamed.jahani2@rmit.edu.au

Course Coordinator Location: Building 80

Course Coordinator Availability: Appointment via email


Pre-requisite Courses and Assumed Knowledge and Capabilities

Required Prior Study:

Course ID 054384 Introduction to Business Analytics


Course Description

The growth in organisations’ ability to collect large amount of data present challenges of unlocking value from such data. Organisations that are capable of unlocking insights from business data are able to improve the decision-making, inform the strategy, thus achieve sustained competitive advantages.

This course is designed to equip you with the advanced models, methods, and tools required for a deep understanding of the latest business analytics techniques. Artificial intelligence, machine learning, heuristics and patterns matching are introduced to cater for the need of the business analytics in modern organisations for unlocking value from business data. Different business problems are chosen to illustrate the effectiveness and applicability of these business analytics techniques.


Objectives/Learning Outcomes/Capability Development

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On successful completion of this course, you will be able to:

CLO1: Identify the appropriate uses for advanced business analytics techniques and tools for complex business data analysis.
CLO2: Critically evaluate the effectiveness and applicability of advanced business analytics techniques and tools in solving complex business problems.
CLO3: Research and investigate the emerging and global trends of business analytics tools and practices in the industry.
CLO4: Apply appropriate advanced business analytic techniques and tools, to inform responsive, evidence-based decision-making.
CLO5: Effectively communicate business intelligence solutions using advanced business analytics techniques in a professional business context.


Overview of Learning Activities

In this course you will be encouraged to be an active learner. Your learning will be supported through various learning activities. These may include quizzes; assignments; prescribed readings; sourcing, researching and analysing specific information; solving problems; conducting presentations; producing written work and collaborating with peers on set tasks or projects.


Overview of Learning Resources

Various learning resources are available online through MyRMIT Studies/Canvas. The lecture notes and workshop notes are posted on Canvas.

RMIT Library provides extensive resources, services and study spaces. All RMIT students have access to scholarly resources including course related material, books, e-books, journals and databases.

Computers and printers are available at every Library. You can access the Internet and Library e-resources. You can also access the RMIT University wireless network in the Library.

Contact: Ask the Library for assistance and information on Library resources and services: http://www.rmit.edu.au/library. Study support is available for assistance with assignment preparation, academic writing, information literacy, referencing, maths and study skills.  Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.


Overview of Assessment

The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows:

Assessment Task 1: 30%
Linked CLOs: 1, 2, 3, 4, 5

Assessment Task 2: 35%
Linked CLOs: 1, 2, 3, 4, 5

Assessment Task 3: 35%
Linked CLOs: 1, 2, 3, 4, 5

Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on practical exercises and by individual consultation.