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BUSA3430 – Business Applications of Artificial Intelligence

2024 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Olivera Marjanovic
olivera.marjanovic@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
COMP2200
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit looks at practical applications of AI systems in a business context, including how AI systems can be deployed, integrated with other business systems, and maintained in the longer term. Some areas that may be covered include the use of recommender systems, text mining, decision support systems and automated assessment of candidates. The unit includes a discussion of the ethical and legal questions raised by the deployment of these systems in a business and of the long-term sustainability of such systems.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

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

  • ULO1: Evaluate the capabilities of modern AI systems against the needs of business
  • ULO2: Assess the sustainability of AI solutions in an industry context
  • ULO3: Describe the issues that arise in deploying AI systems as part of a larger information systems offering
  • ULO4: Evaluate stakeholder focused AI algorithms and systems
  • ULO5: Communicate effectively about artificial intelligence topics to experts and non-technical audiences
  • ULO6: Successfully work in teams to achieve group and organizational objectives

General Assessment Information

Late Assessment Submission Penalty (written assessments)

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A1-hour grace period is provided to students who experience a technical concern.

For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.

Assessment Tasks

Name Weighting Hurdle Due
AI Industry Case Study 30% No Week 7
In-term quizzes 20% No Week 5, Week 9 and Week 12
Weekly Tutorial Participation 10% No Weeks 2-13
Team Project 40% No Week 13

AI Industry Case Study

Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 34 hours
Due: Week 7
Weighting: 30%

 

Students will be required to analyse one or more AI case studies using the frameworks covered in class.

 
On successful completion you will be able to:
  • Evaluate the capabilities of modern AI systems against the needs of business
  • Assess the sustainability of AI solutions in an industry context
  • Describe the issues that arise in deploying AI systems as part of a larger information systems offering
  • Evaluate stakeholder focused AI algorithms and systems
  • Communicate effectively about artificial intelligence topics to experts and non-technical audiences

In-term quizzes

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 11 hours
Due: Week 5, Week 9 and Week 12
Weighting: 20%

 

Students will be required to complete two or more short quizzes designed to test the AI fundamentals covered in weekly classes.

 
On successful completion you will be able to:
  • Evaluate the capabilities of modern AI systems against the needs of business
  • Assess the sustainability of AI solutions in an industry context
  • Describe the issues that arise in deploying AI systems as part of a larger information systems offering

Weekly Tutorial Participation

Assessment Type 1: Participatory task
Indicative Time on Task 2: 0 hours
Due: Weeks 2-13
Weighting: 10%

 

Students will be required to actively contribute to weekly tutorials in different ways that encourage and value different learning styles and needs.

Attendance does not count as contribution.

 
On successful completion you will be able to:
  • Evaluate the capabilities of modern AI systems against the needs of business
  • Assess the sustainability of AI solutions in an industry context
  • Describe the issues that arise in deploying AI systems as part of a larger information systems offering
  • Evaluate stakeholder focused AI algorithms and systems
  • Communicate effectively about artificial intelligence topics to experts and non-technical audiences

Team Project

Assessment Type 1: Project
Indicative Time on Task 2: 40 hours
Due: Week 13
Weighting: 40%

 

This assignment consists of two components: Group project (30 marks) and individual reflections on the project (10 marks).

Students will be required to complete a group project related to business applications of AI in an organisational setting, taking a business perspective. Additionally, each team member will be required to complete an individual reflection on the project.

 

 
On successful completion you will be able to:
  • Evaluate the capabilities of modern AI systems against the needs of business
  • Assess the sustainability of AI solutions in an industry context
  • Describe the issues that arise in deploying AI systems as part of a larger information systems offering
  • Evaluate stakeholder focused AI algorithms and systems
  • Communicate effectively about artificial intelligence topics to experts and non-technical audiences
  • Successfully work in teams to achieve group and organizational objectives

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

The unit is comprised of 13 weekly classes (2h-hour lecture + 1h-tutorial), held on-campus in weeks 1 to 13. The unit is not designed for remote learning.  Weekly in-person attendace is expected in both lectures and tutorials.

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via AskMQ, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2024.04 of the Handbook