• Apply programming and optimization for data analysis in process safety.
• Use Excel, Visual Basic, and Python for data processing and visualization.
• Perform risk analysis using Monte Carlo simulation.
• Apply machine learning and predictive analytics for hazard prediction.
• Detect anomalies and patterns for enhanced process safety.

This course covers essential data analysis techniques for process safety, emphasizing programming, optimization, and predictive analytics. Students will learn tools like Excel, Visual Basic, Python, and AI for analyzing and visualizing data. Key topics include risk analysis, Monte Carlo simulation, machine learning, and anomaly detection, with applications in hazard prediction.

1. Sagit Valeev and Natalya Kondratyeva, Process Safety and Big Data

1. Introduction to Programming
2. Numerical Computation and Optimization
3. Macro and Microsoft Excel
4. Visual Basic
5. Optimization
6. Data Visualization
7. Introduction to Artificial Intelligence
8. Introduction to Python
9. Risk Analysis Using Monte Carlo Simulation
10. Introduction to Machine Learning
11. Data Preprocessing and Visualization
12. Predictive Analytics for Hazard Prediction I (Regression and Classification)
13. Predictive Analytics for Hazard Prediction II (Time Series)
14. Anomaly Detection Techniques