Assessment 3 Information

Your Task

Develop a real-world Machine Learning or AI project plan/proposal based on the learnings from the subject.

Assessment Description

This assessment seeks to simulate a real-world task that you may have to undertake in the

future. Therefore, the assignment is non-prescriptive and requires you to pose a relevant, small,   creative and significant problem to solve that could result in benefits to the organisation of choice.

In this assessment, you need to consider an organisation in an industry of your choice and   articulate the steps this organisation needs to take to enable Machine Learning and/or AI for data-driven decision making. You are required to analyse a sample data set to demonstrate  expected AI/ML outcomes.

You need to be familiar with the organisation and industry (e.g., where you have worked or are  working, a future start-up company), NOT an organisation such as Amazon/Boeing/Qantas etc.

Well-reasoned use of Generative AI is encouraged. However, generic and irrelevant content will  be heavily penalised in the marking.

The report should address:

o Why AI would help this organisation given their current operations

o What Machine Learning techniques you would recommend

o An example of the predictive model using sample data

o Deployment considerations for the model

o The benefits for the organisation clearly articulated with estimates of expected revenue/profits or Return on Investment

Assessment Instructions

•    By Week 9 identify a company and industry you are familiar with that would benefit from Machine Learning/AI. Note:

o The application needs to be based on Machine Learning/AI (not some other aspect of analytics).

o Focus on a single, well defined (small) application.

o Sample datasets maybe sourced from:

. an organisation. if you work there

. public repositories such as kaggle.com and https://archive.ics.uci.edu/ml/datasets.php,

. Open government data such as abs.gov.au

•    By Week 12 draft some preliminary points pertaining to the report in class. You are

encouraged to consider the current mode of operation, possible inefficiencies,

available data and how this data may be used to provide efficiencies based on the

concepts and techniques covered in the subject. Think of yourself as a consultant or a founder.

•   Your lecturer will advise on the appropriateness of your choice and proposed methodology regarding the requirements for the assessment.

•    Include a list of references that is directly related to the content. Each reference needs to be linked to at least one specific point in the content of your assessment. It is

expected that you will have at least six relevant references.

•    Briefly describe or show how your solution maybe enhanced by Quantum Machine Learning.

•    Describe or show how you could leverage ChatGPT to enhance your solution.

•    Upload the file that contains your prediction model (in Orange, Exploratory or Python) to the dropbox provided on the assessment page.

•   Submit report in Turnitin.

Important Study Information

Academic Integrity Policy

KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.

What is academic integrity and misconduct?

What are the penalties for academic misconduct?

What are the late penalties?

How can I appeal my grade?

Click here for answers to these questions:

http://www.kbs.edu.au/current-students/student-policies/.

Word Limits for Written Assessments

Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.

Study Assistance

Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click herefor this information.