Assignment-1 Guideline:
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Assessment Task 1 |
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Intent |
This assessment task addresses the following subject learning objectives (SLOs) : 1 and 2. |
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Task |
In this assignment, students will give a data exploration repor t on their work in the project. Their group will d escribe the results of their data exploration and feature engineering by using the SAS Viya tool . The report should cover the business problems , characteristics of the data , and transformation of the data. The report should be structured and presented in line with professional industry report format. |
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Length |
15 pages max in an 11 or 12-point font. |
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Criteria Linkages (Please insert addition rows i n table where required) |
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Assessment Criteria |
Weight (%) |
SLO |
GA |
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1 |
Depth of understanding of the business problem and quality of data exploration results. |
100% |
1, 2 |
D, E |
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2 |
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3 |
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4 |
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5 |
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6 |
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Assessment Task 1: Data Exploration
Objective: The main objective of this assessment task is to apply data exploration and feature engineering techniques to real-world business problems.
Relevant Learning Objectives :
• Subject Learning Objectives: SLO 1
• Course Intended Learning Outcomes: CILO D.1
Format:
• Type: Report
• Work: Group assignment, but each member will be individually assessed.
Weightage: 30% of the overall grade.
Task Description: Students are required to:
1. Form groups of 2-3 (you may increase group size at max of 5 members based on your tutor’s choice) members.
2. Select a dataset similar with the COMMSDATA (in SAS Viya Course) or any other
existing datasets is available for classification task. Selecting a right dataset is key in this assignment. Please ensure to select a large dataset (over 1000 data points).
3. Select a predictive business analytics task based on the chosen dataset.
4. Collaboratively analyze both the chosen business problem and its associated dataset.
5. Submit a report, detailing:
o The business problem they aim to solve.
o Characteristics of the chosen dataset.
o Data transformation processes applied.
o Proposed method to address the data mining problem.
Additionally, the report should also describe:
• The composition of the group.
• Roles and responsibilities of each team member.
• A proposal for addressing the data mining problem.
• A comprehensive plan outlining how they intend to solve the problem.
Assessment Criteria: Assignments will be evaluated based on:
1. Description of business problem
2. Quality and feasibility of the proposal and plan.
3. Data exploration and initial findings:
-Quality of pre-processing
– Quality of initial findings
4. EDA Visualisation
Submission Details:
• Format: Electronic copy
• Platform: Canvas for report and SAS Viya (in Exchange Folder) for upload the pipeline
• Maximum Length: 15 pages (using 11 or 12-point font)
• Due Date: 11.59pm, Friday 8 September 2023
• Feedback Timeline: Feedback with marks will be provided within 2 to 3 weeks after submission.