Artificial Intelligence and Machine Learning for Business

Unit code: BCO7007 | Study level: Postgraduate
(Generally, 1 credit = 10 hours of classes and independent study.)
City Campus
Online Real Time
VU Brisbane
VU Sydney


Artificial Intelligence (AI) and Machine learning (ML) have become widely used and sought after in data rich business environment. They are indispensable for making business decisions with leveraging big data across all areas of business operations. The unit introduces students to foundations of ML and AI by building solid understanding of underlying concepts, algorithms and techniques. This is supported by hands on experience with current platforms and tools such as TensorFlow and Keras. The students are exposed to real life scenarios of ML and AI applications to implement analytical solutions to generate meaningful business insights. This unit covers supervised and unsupervised ML as well as introduces students to deep learning, and applications in natural language and image processing. Upon completion of the unit, the graduates are able to develop and evaluate business solutions to optimise business operations and offer benefits and cost savings to businesses in achieving competitive advantage.

Learning Outcomes

On successful completion of this unit, students will be able to:

  1. Contextualise issues of business data to develop ML and AI solutions for improving business decisions in contemporary organisations;
  2. Justify the selection, assessment, design, integration, and formation of data models effective to ensure appropriate visualisation and prediction that contribute to meet business needs;
  3. Critically review the selection and application of industry focused data processing approaches and solutions; and,
  4. Appraise and communicate appropriate AI and ML solutions based analytics implementation in organisations and authenticate recommendations with reference.


For Melbourne campuses

Assessment type: Test
Grade: 25%
A range of machine learning exercises based on solving business problems in the software environment.
Assessment type: Assignment
Grade: 35%
Dataphone: a Kaggle style data competition to build and evaluate a ML solution and presentation - Group
Assessment type: Report
Grade: 40%
Based on a real-world scenario develop and apply major models and algorithms for machine learning

Required reading

Selected readings will be made available via the unit VU Collaborate site.

As part of a course

This unit is studied as part of the following course(s):

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