Cyberpunk Data Science Portfolio 🌐📊

Welcome to my interactive data science portfolio! This project showcases my experience, academic credentials, and machine learning projects within a high-fidelity, cyberpunk-themed terminal environment built with Three.js and vanilla CSS.

🔗 Live Link: https://aliibtisam.vercel.app

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🚀 Key Visual & Technical Features

• 🧠 Three.js Neural Network: Interactive 3D point cloud simulation showing live interconnecting nodes and lines that react to cursor movements.
• 🔴 Dynamic Neon Red/Orange Theme: Custom aesthetic with retro-futuristic grid systems and glowing telemetry status indicators.
• 🔢 Stats Boot Sequence: Custom counter animations calculating key academic and ML metrics upon entering the viewport.
• 💬 Bilingual Support: Instant toggle option between English (EN) and German (DE).
• 📱 Fully Responsive Layout: Seamless experience across mobile, tablet, and desktop screens.
• 🛡️ Secure Telemetry Contact Form: Custom-intercepted terminal contact submission powered by FormSubmit.

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🛠️ Data Science & Analytics Stack

• Machine Learning: Scikit-Learn, Random Forest, Logistic Regression, Predictive Modeling, Feature Engineering
• BI & Visualization: Power BI, Tableau, Data Viz, Excel
• Data Engineering: SQL, API Integration, QA Testing, Git / GitHub
• Languages: English (Full Professional), Urdu (Native), German (Elementary)

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📁 Featured Projects

📈 SmartStock — Retail Demand Forecasting

An end-to-end sales forecasting pipeline processing 50,000+ transactions using SQL extraction, Machine Learning modeling, and automated inventory classification across 10 store segments.

• Metrics: $R^2$ = 0.9576 | MAE = 72.69 | $-35%$ Stockouts | $+23%$ Accuracy
• Keywords: Python, Random Forest, SQL, Power BI, Feature Engineering, Time-Series

👥 Customer Churn Prediction

Exploratory Data Analysis (EDA) on 7,000+ telecom records, identifying 6 high-risk churn segments. Developed predictive classifiers for precision retention targeting.

• Metrics: 87% Recall | 7K+ Records | $+12%$ Precision | 6 Segments
• Keywords: Python, Logistic Regression, Random Forest, EDA, Seaborn, Scikit-Learn

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🎓 Academic Credentials

• Bachelor of Data Science (Honours) — Albukhary International University (AIU), Malaysia
  • Oct 2025 – Expected 2028
  • CGPA: 3.89 / 4.0
  • Scholarship: Awarded Fully Funded Scholarship 🏆

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⚡ Setup Locally

1. Clone the repository:

   git clone https://github.com/aliibtisam1001/Personal_Portfolio.git

2. Navigate to the folder:

   cd Personal_Portfolio

3. Run a local development server:
   • Using Python: python -m http.server 8000
   • Using Node: npx http-server
4. Open your browser and navigate to http://localhost:8000

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📬 Connect with Me

• 💼 LinkedIn: aliibtisam1001
• 💻 GitHub: aliibtisam1001
• 📧 Email: aliibtisam1001@gmail.com