Description
Please find the attached assignment 3 details for your action.
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Assessment 3 Information
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DATA4800
Artificial Intelligence and Machine Learning
Machine Learning/AI for a Business Problem
Written Report
2500
Words
40 %
(+/-10%)
40
Turnitin
Individual report via Turnitin due Monday, Week 13 (23.55pm AEST)
Your Task
Develop a real-world Machine Learning or AI project plan/proposal based on the learnings from the
course.
Assessment Description
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.
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 The benefits for the organisation clearly articulated with estimates of expected
revenue/profits or Return on Investment
Assessment Instructions
Page 1
•
By Week 9 identify a company and industry you are familiar with that would benefit
from Machine Learning/AI. Note: The application needs to be based on Machine
Learning/AI (not some other aspect of analytics).
•
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
Kaplan Business School Assessment Outline
founder.
•
Your facilitator will advise on the appropriateness of your choice and proposed
methodology with regard to the requirements for the assessment.
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 here for this information.
Page 2
Kaplan Business School Assessment Outline
Assessment Marking Guide
This assessment will be marked on the grounds of whether or not the following competencies are
present.
Forecasting for a Business Problem
Section
Choice of Topic
Problem Statement
Methodology
Presentation
Criteria
Students should identify a
forecasting-based application in a
real (or realistic) business and
industry.
Students should clearly articulate
the needs and goals for
MachineLearning/AI from a
business perspective.
Students should describe the
method based on knowledge and
techniques covered in the course.
Students will be graded on
• Structure, style and visuals.
• Creativity in document,
method and solution.
Page 3
Marks Available
8 marks
10 marks
15 marks
3 marks
4 marks
Kaplan Business School Assessment Outline
Further points regarding assessment 2 and 3
by Professor – Wednesday, 20 January 2021, 9:01 AM
Number of replies: 0
Hi,
The typical approach to solving problems in Analytics is to reduce the problem to its simplest form. In
most workplace scenarios you need the hardest task is to find the right question – there is no predefined question that you are answering. Your assessments intend to capture this real-world scenario.
Hence,
1. Please think of a use case before selecting an application for assessment 2 (it simplifies an
otherwise open ended problem). The application can be from outside the list of 10 suggested
applications but if so validate your choice with the lecturer. Remember the applications are based on
neural networks and deep learning that we have covered for the last 3 weeks.
2. Remember, this class is about prediction not forecasting!
3. Therefore, assessment 3 is not the same as DATA 4400 – the use case will be different. If you don’t
understand this please contact your lecturer or me.
4. You are not restricted to a specific tool or method if analysing a sample dataset- use whatever is
appropriate and comfortable for you (including web based tools).
5. Hopefully, you will choose “use cases” that are relevant to your past, present or future work
places/interests so that you are able to leverage your work beyond the assessments.
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