Due on November 26, 2025, end of day
This assignment uses data from the Nata Supermarkets: Customer Analytics case. The dataset contains information about supermarket customers — including their demographics, spending habits across product categories, and how long they’ve been customers.
You will apply predictive analytics to predict customers' spending on certain product categories.
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Read the case description (provided separately in the course outline). It introduces Nata Supermarkets’ business context and explains what each variable in the dataset represents.
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Open the Colab Notebook The notebook outlines the details tasks to be completed.
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Answer each question directly in the notebook
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Use code cells for your Python code.
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Use short text cells (Markdown) to answer questions.
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Make sure to include your name and student number and save your colab notebook to Github.
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By completing this assignment:
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Practice skills in predictive analytics.
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Develop skills to interpret model results and provide business insights.
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The customer dataset (to be loaded to Colab)
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Assignment_3_notebook.ipynb— your Colab notebook with questions -
README.md — this instruction file
Submit to GitHub Classroom before the due date. Make sure all code cells run correctly and outputs are visible.