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Interactive AI-powered statistics playground that visualises probability concepts like dice rolls, coin flips, and normal distributions using Python, Pandas, and Streamlit.

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📊 Probabilistic Risk Assessment Engine

A professional-grade interactive dashboard for modelling uncertainty in random processes and evaluating basic cyber risk scenarios using probabilistic simulation.

This project demonstrates real-world analytical thinking, risk modelling principles, and practical data visualisation techniques commonly used in cybersecurity, risk analysis, and decision science roles.


🚀 Project Overview

The Probabilistic Risk Assessment Engine is an interactive system built to simulate, analyse, and visualise:

  • Random event outcomes (coin flips & dice rolls)
  • Cyber threat likelihood under varying defensive conditions

It allows users to explore how probability behaves in practice and how risk changes as system parameters evolve.

This is designed to feel like an analyst tool — not a classroom demo.


🎯 Key Capabilities

🎲 Random Event Simulation

Model stochastic behaviour across large trial runs:

  • Coin flip outcome distribution
  • Dice roll probability convergence
  • Theoretical vs observed probability comparison
  • Real-time graphical plotting

🛡️ Threat Risk Assessment

Simulate cyber attack success probability based on:

  • Base attack likelihood
  • Defensive strength level
  • Scenario volume

Outputs include:

  • Adjusted risk metrics
  • Visual risk indicators
  • Scenario breakdown tables

🖥️ Live Interface Preview

(GIF DEMO COMING SOON)

This section will showcase a short animated demonstration of:

  • Switching modules
  • Running simulations
  • Interpreting risk outputs

📷 Screenshots

Dashboard Interface

Add screenshot here after deployment

[ Screenshot Placeholder ]

🧠 Technical Highlights

  • Streamlit-based interactive UI
  • Modular simulation architecture
  • Probabilistic modelling logic
  • Statistical analysis pipeline
  • Visual risk interpretation system

🛠️ Tech Stack

  • Python
  • Streamlit
  • NumPy
  • Pandas
  • Matplotlib

📁 Project Structure

ai-probability-playground/
│
├── main/
│   ├── app.py            # Main Streamlit interface
│   ├── simulate.py       # Simulation logic engine
│   ├── visuals.py        # Visualisation utilities
│   └── stats.py          # Statistical helpers
│
├── requirements.txt
├── README.md
└── .gitignore

✅ Phase 1 Completion Status

✔ Clean UI structure ✔ Modular simulation system ✔ Risk modelling interface ✔ Professional layout ✔ Ready for deployment


📌 How to Run Locally

pip install -r requirements.txt
streamlit run main/app.py

🔮 Planned Enhancements (Next Phases)

  • Advanced risk modelling algorithms
  • Historical risk trend analysis
  • Interactive scenario builder
  • Exportable risk reports

👤 Author

Built as a passion-driven project exploring uncertainty, probability, and how risk behaves in dynamic systems. This work reflects a deep interest in turning abstractical concepts into interactive, meaningful tools that help people understand how decisions, chance, and protection mechanisms interact in the real world.

This engine is designed to evolve — incorporating richer models, stronger simulations, and more expressive visualisations as the system grows.

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Interactive AI-powered statistics playground that visualises probability concepts like dice rolls, coin flips, and normal distributions using Python, Pandas, and Streamlit.

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