FDP - Data Science Pipeline: End-to-End Workflow

Topic: Data Science Pipeline | Host: Jodhpur Institute of Engineering & Technology (JIET)

📂 Contents

File	Description
fdp-colab-content/student_stress_data.csv	Synthetic dataset of 300 student records for stress level prediction
fdp-colab-content/FDP_Student_Stress_Prediction.ipynb	Google Colab notebook — zero setup required
fdp-colab-content/FDP_PreRead_StudentStress.pdf	Pre-read material for FDP attendees
fdp-colab-content/generate_dataset.py	Dataset generator script
fdp-colab-content/pre_read.html	Pre-read material source (HTML)

🎯 Dataset Overview

300 student records × 8 columns

• Target: Stress_Level (0 = Not Stressed, 1 = Stressed)
• Features: Department, Attendance_Level, Favorite_Color, Weekly_Study_Hours, Assignment_Submission_Pct, Backlogs_Count

🚀 Using the Colab Notebook

1. Open the notebook in Google Colab
2. Run all cells — no installation needed
3. Dataset auto-loads from raw GitHub URL

📊 Pipeline Steps

1. Data Loading
2. Exploratory Data Analysis
3. One-Hot Encoding (Department, Attendance_Level, Favorite_Color)
4. Random Forest Classification
5. Model Evaluation
6. Feature Importance Visualization

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Part of Gyannetra's FDP workshop series