Academic Misconduct

Academic Misconduct
Work which is submitted for assessment must be your own work. All students should note that the
University has a formal policy on Academic Integrity and Academic Misconduct (including plagiarism)
which can be found here.
Plagiarism: We are aware that assignment solutions by previous students can sometimes be found posted
on GitHub or other public repositories. Do not be tempted to include any such code in your submission.Using code that is not your own will be treated as “poor academic practice” or “plagiarism” and will be
penalized.
To avoid the risk of your own work being plagiarised by others, do not share copies of your solution, and
keep your work secure both during and after the assignment period.
Collusion: This is an individual assignment: working together with other students is not permitted. If
students submit the same, or very similar work, this will be treated as “collusion” and all students
involved will be penalized.
Contract cheating: Asking or paying someone else to do assignment work for you (contract cheating) is
considered gross academic misconduct, and will result in termination of your studies with no award.
Report Template
Note that a penalty will be applied to each section that goes over the word limit. This penalty will be
proportional to how many words over the limit you are – e.g. 10% over the word limit will incur a
10% penalty.
1. Introduction (Word Limit: 250 words – 10 marks)
Summarise the problem the company is asking you to solve. Demonstrate that you can connect it to the
data by mentioning the variables that are most likely to be relevant to the problem.
2. Data Cleaning (Word Limit: 250 words – 20 marks)
What data cleaning was required for this dataset? What techniques did you employ to correct for them?
3. Exploratory Data Analysis (Word Limit: 500 words – 25 marks)
Explore the dataset and make, at least, 3 interesting observations that you have learned from the data. Use
appropriate visualisations to support your findings.
4. Descriptive Analytics (Word Limit: 500 words – 25 marks)
Think about questions that might be useful for your client and that can be answered using descriptive
analytics. Answer such questions using this type of analysis. Report the questions, why they are important
for your client, and the answers.
5. Machine Learning (Word Limit: 500 words – 20 marks)
Now that you understand the business’s needs and concerns, and the data that they have access to, try to
answer the enquiries of your client using machine learning. You do not need to implement this.
Instead, just specify what question(s) you could answer with machine learning, what type of problem it is,
and what kind of model you would use. Justify your choices in model