AB0403 Decision Making with Programming and Data Analytics – Presentation Recording (2025/26 Semester 1)

(4-5 students in a group).

Individual Video Presentation Requirements

 

In this individual video presentation, you are required to:

• Pick an analysis you want to present from the proposed scenarios. Each scenario provides possibilities of different interpretations and analyses. Each member within a group is to work on a unique analysis. Add comments to specify your interpretation at the start of your file.
• Prepare a Python solution to address the requirements specified in the chosen scenario.
• Prepare a presentation recording to explain how you address the requirements, the code important to the solution you suggested and illustrate the result based on the given data in the file.
• Reflect on your learning journey in the presentation recording, e.g., what have you learnt, which of the topic(s) you learnt is/are useful in solving/analysing business problems, etc.

Objective and Technical Constraints

 

The objective of this presentation recording is to assess your understanding of the first 7 weeks of content and how you apply that in real-life scenarios in different contexts. You are to make use of the python coding knowledge you have acquired in the first 7 weeks (other topics such as DataFrame, external libraries, etc, are not allowed) to prepare a technical presentation to explain your suggested solution.

• You are not encouraged to use Pandas for this work. Pandas is the topic to be assessed under the Group Project.
• In your presentation, you are required to focus on how you address the requirements, explain the flow of your codes, codes that are important to your solution and illustrate the result based on the given data file of the given scenario.
• Note that you are NOT supposed to explain your codes line by line.

 

Video Presentation Details and Submission

 

• The duration of the video should be about 2-3 minutes. You are advised to adhere to the time limit strictly.
• You are to prepare the recording beforehand and submit it before the due date.
• Each group member will record his/her own video and ensure that the hyperlink to the video is included in the FIRST LINE of your code file submitted.
• You can use Zoom, Teams, or YouTube for recording. If you use other software to record into mp4 file, upload online to YouTube, OneDrive, or other cloud storage and obtain a shareable link (do not submit video files).
• In the case of YouTube, indicate as restricted and submit only the shareable link information.
• Your face must be visible throughout the video presentation.
• Double-check the link before submission, and ensure it is viewable without needing to log in. A penalty will be imposed if the link is not viewable by the grader.

 

Company Background and Data

 

 

Background of company: Nanyang Analytics Pte Ltd is a research firm that works with the government to collect data related to employment. It has collected extensive data from 2007 to 2024 and the company is looking to present the figures to explain the trends of education and employment. Your team is tasked with generating comprehensive insights on the trends and each member must contribute a unique perspective.

 

Given the data files:

• Dataset A: Employed Residents Aged 15 Years And Over By Industry And Age Group
  • Values represented is in 1,000. e.g. 0.8 is actually $0.8\ast 1000=800$
  • And numbers that are not available are marked as “na”, and values that are statistically negligible are marked as “-“.
• Dataset B: Employed Residents Aged 15 Years And Over By Occupation And Age Group
  • Same as Dataset A
• Dataset C: Singapore Residents Aged 25 Years & Over By Highest Qualification Attained (HQA), Sex And Age Group
  • The numbers are represented as is.

 

Possible Scenarios for Analysis

 

The following are some of the possible scenarios you can work on, you are required to use the dataset provided to present your arguments and you may use more than one data file to support your analysis.

• Is access to education equal between the genders? Are there any changes over the years?
  • E.g. User can key in the year and the program will show a table with different education level attained, divided by genders. User may then choose a range of years to display or dive into specific age groups to compare.
• Are the residents progressing through the career ladder? What about the education level attained? Any similarity or dissimilarity?
  • E.g. User can enter a year and be presented with a table showing the number of people and percentage in each occupation for the year. User may pick an occupation and be presented either with the trends over the years, or the number of people in different age group in that occupation.
• Which industry sectors provide the greatest employment opportunities? Are there preferences among the age-ranges for industries?
  • E.g. User can enter a year and be presented with a table showing the number of people and percentage in each industry for the year. User may pick an occupation and be presented with the trends over the years by age groups or pick an age group and show the trend over the years by occupations.
• How does industry growth in employment link to the level of education qualification of the society?
  • E.g. User can choose an industry and an education level, and the program should show the trend of the number of people holding the qualification, and the number of jobs provided by that industry across all the years.
• How the demand for different occupations changes over time?
• Which occupations show the highest growth rates over time?
• Or other questions that can be answered from the dataset.

Python Program Requirements

 

For each submission, your python program is required to complete the following:

1. Read in the given data file(s)
2. Allow user to enter a certain filter criterion.
3. Tabulate a table that address the scenarios according to the filter criteria. (note: You are NOT allowed to use the tabulate module, you are encouraged to use string formatting to present neat output)
4. Generate suitable analytics conclusion based on the table.
5. Allow the program to loop till a termination point is detected.
6. Generate a summarised analysis to help user reconcile the queries made during the session.
7. Provides meaningful comments throughout your codes:
   • clarify purpose of key code blocks
   • describe the flow of your codes and how each part contributes to the overall solution
   • highlight critical sections of your code that are essential to your solution
   • keep comments clear and concise
   • these comments should be consistent with your presentation deliverables

 

Deliverables (Due Date: Week 8’s Saturday 7pm)

 

• Python code file: in .py format (ensure the recording link is inserted in the first line of code). Replace the filename from the given python file with your seminar number (x), group number (y) and student number (Uz).
• The PowerPoint file you use to present in pdf format.
• Signed declaration form.

 

General Requirements and Academic Integrity

 

• All work must be done in the Python programming language.
• Graders should be able to run your code without additional installation and setup.
• Graders may select individuals for interviews to answer questions related to submitted works as part of the random check or to ascertain academic integrity.
• All submitted works should be done originally by you only, which means no outsider(s) should be involved in the work.
• Submitting work done by others or plagiarised works is an act of academic dishonesty. Academic dishonesty affects the University’s reputation and devalues the degrees offered. The University will impose serious penalties on students who are found to have compromised academic integrity.
• You are not encouraged to use or import the following Python modules/libraries: [List of not encouraged Python modules/libraries including json, streamlit, gradio, tkinter, PyQt5, kivy, flask, django, statsmodels, scikit-learn, pycaret, tensorflow, keras, pytorch, nltk]
• In addition, your Python codes should not contain Python classes since it is a topic not within the scope of this module.
• You will be assessed based on how well you use and apply the knowledge and skills taught in the first 7 weeks of this module.

 

AI Assessment Scale (AIAS)

 

The permitted AIAS for this module is Level 3: Al-assisted editing.

• You are allowed to use Gen-Al to improve the quality of your work but not on content and source code generation.
• Gen-Al can be used for code refinement. The original work (before the use of Gen-Al) and the refined work (after the use of Gen-Al) should both be submitted.

 

Data Files

 

• A. Employed Residents Aged 15 Years And Over By Industry And Age Group.csv
• B. Employed Residents Aged 15 Years And Over By Occupation And Age Group).csv
• C. Singapore Residents Aged 25 Years & Over By Highest Qualification Attained (HQA), Sex And Age Group.csv

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