Foundations of Data Science
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FIT5145: Foundations of Data Science
Assignments 1 & 3: Business and Data Case Study
1. Assignment 1 (Proposal): Write a proposal document to introduce a data science project that you
are studying. The due date of Assignment 1 is: Sunday, 31 March 2024, 11:55 PM (Week 5).
2. Assignment 3 (Report+Presentation): Write a report on your case study of the data science
project and prepare a 4-minute presentation on your project. The due date of Assignment 3 (the
final project report and presentation slides) is: Sunday, 19 May 2024, 11:55 PM (Week 11) and
the presentation will be held in the Week 12 applied class.
- Both Assignment 1 and 3 are individual assignments.
- Please do NOT zip your submission files. Zip file submission will have a penalty of 20%
of the total mark of the assignment.
Focus of the study
This case study needs to analyse (“study”) a data science project relevant to a business scenario (“the
case”). There are a couple of ways you can choose to do the case study. For instance, you may choose to
study how an existing data science project has been implemented in a particular sector such as
transportation or healthcare. The project chosen is NOT limited to those already established or
completed. You can propose an entirely new and novel project of your own, e.g., how can the Australian
government tackle bushfire or flood by making use of Twitter data? That being said, you can either study
an existing data science project or propose a completely new data science project. Talk to your tutors
about any proposed project you are interested in.
Assignment 1: Proposal (15%)
Weight: 15% of the unit mark
Submission format: one PDF file
Size: up to 700 words.
What you need to do:
● Choose a data science project.
● Write the initial two sections, Project Description and Business Model (References as well to
support your project) of the report, as detailed in the specification of Assignment 3: Report +
Presentation below. This assignment is worth 15% of your unit mark.
We have developed a system named FLoRA to support you to accomplish Assignment 1, which you may
access via: https://www.floraengine.org/moodle/my/courses.php. You are expected to work with the
chatbot embedded in FLoRA, powered by cutting-edge Generative Artificial Intelligence (GAI)
technology GPT-4, to accomplish the assignment. You can discuss the assignment requirements with the
GAI-powered chatbot, seek suggestions for potential project topics in a specific domain (e.g., education,
agriculture, sports, and finance), and gather information relevant to a specific project topic by conversing
with the chatbot. Even more, you may send the proposal draft to the chatbot and seek feedback for further
improvement.
Please notice:
● You should log in to the FLoRA platform by using your Monash email account and we will send
you login credentials via emails.
● You are only expected to use FLoRA to accomplish Assignment 1, though you may use it for
Assignment 3 as well, it is not mandatory.
● The conversational data you generate when interacting with the GAI-powered chatbot will be
used for textual analysis in Assignment 4 in this unit. That is, the conversational data will be
shared with the whole class and thus please only discuss your data science project with the
GAI-powered chatbot and do not disclose any personal or sensitive information during this
process.
After logging to the platform, you will see there are four modules required to accomplish Assignment 1,
as shown below:
Module 1: Pre-task activity
● Please provide information about yourself as well as your prior knowledge and experience in
data science and GAI.