Available in 2024
Course code

BUSA3001

Units

10 units

Level

3000 level

Course handbook

Description

Businesses and governments have massive data available to them with which to make systematic strategic decisions. Artificial Intelligence (AI) and machine learning can process and provide fast turnover of these very large amounts of information. This course is designed to provide students with knowledge related to established and emerging developments of AI in organisations using real-world examples. Applications of AI in various areas including finance, fraud detection, customer relationship management, and human resources management will be discussed.


Availability2024 Course Timetables

Newcastle City Precinct

  • Semester 1 - 2024

Learning outcomes

On successful completion of the course students will be able to:

1. Demonstrate an understanding of the main concepts of Artificial Intelligence and machine learning

2. Demonstrate understanding of how to operationalise Artificial Intelligence and machine learning

3. Identify key areas to apply Artificial Intelligence and machine learning techniques within a business organisation

4. Discuss advantages and the risk of using Artificial Intelligence and machine learning techniques for strategic decision making


Content

The topics in this course include:

  1. Introduction to artificial intelligence (AI)
  2. Business applications of machine learing and personalisation
  3. AI-driven business and government transformation
  4. AI in the organisational structure
  5. Benefits and risks of using AI for decision making

Assumed knowledge

BUSA1001 Introduction to Business Information SystemsBUSA2001 Big Data Analytics


Assessment items

Quiz: Mid Term Quiz

Case Study / Problem Based Learning: Case Study and Report on Artificial Intelligence (AI) in business

Formal Examination: Final Exam


Contact hours

Semester 1 - 2024 - Newcastle City Precinct

Integrated Learning Session-1
  • Face to Face On Campus 2 hour(s) per week(s) for 13 week(s) starting in week 1

Course outline