Client Work (Final Project) | COMP 302 Coffee Store ML Analysis | McGill University

Student | Client Work (Coding + Report) | COMP 302 Inventory Optimization | McGill University

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This long-format video presents the full submission of a Final Python Team Project for the course COMP 302 – Programming Languages and Paradigms under the Bachelor of Computer Science program at McGill University, Canada.

📘 Course Code: COMP 302
📕 Course Title: Programming Languages and Paradigms
🏫 University: McGill University
🎓 Program: Bachelor of Computer Science
📑 Assignment Type: Python Final Team Project (Coding + Report)

📌 Project Overview
The project involves analyzing real inventory data from 132 coffee shops worldwide and building predictive models for sales forecasting, stock optimization, and waste reduction. Using Python, data science libraries, and ML models like Random Forest, XGBoost, and LSTM, the team built interactive dashboards and made impactful recommendations.

✅ Outcomes:
This project highlights teamwork, data preparation, time series forecasting, and real-world business insights — essential skills for aspiring AI engineers and data scientists.
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