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Computer Modelling, Big Data Analytics, and AI Utilisation in Fire & Explosion Engineering and Safety

Master digital technologies that are shaping the future of fire and explosion safety
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  • 7-8 Sep 2026
  • Registration open
  • In-person
  • CAPE, Level 8, Permata Sapura Tower, Kuala Lumpur
  • 3,500
  • HRDC claim: Register at least 14 days prior to training

Why should I take this course?

Harness the power of CFD, big data analytics, and AI to transform fire and explosion safety engineering. This practical course equips engineers and safety professionals with hands-on experience in FDS, ANSYS, Python, and machine learning, enabling them to model fire and explosion scenarios, analyse complex datasets, and apply predictive analytics for smarter, data-driven safety decisions.
This course introduces the application of computer modelling, big data analytics, and artificial intelligence (AI) in modern fire and explosion engineering and safety. Participants will gain a solid understanding of computational techniques used to model fire and explosion scenarios, evaluate safety performance, and support risk-informed decision-making. The programme explores the role of advanced digital technologies in enhancing fire safety, process safety, and industrial risk management.

Combining theory with practical applications, the course covers Computational Fluid Dynamics (CFD), Fire Dynamics Simulator (FDS), ANSYS, Python programming, machine learning, and data science fundamentals. Through hands-on case studies and real-world examples, participants will learn to develop, validate, and interpret fire and explosion models, apply AI-driven analytics, and leverage predictive techniques to improve safety performance and engineering outcomes.

Learning Outcomes

Explain the principles of Computational Fluid Dynamics (CFD), big data analytics, and AI in fire and explosion engineering

Apply Python and machine learning techniques to analyse fire and explosion data and support predictive safety assessments

Develop and evaluate fire and explosion models using industry-standard CFD tools such as FDS and ANSYS

Interpret modelling and analytical results to enhance fire safety, process safety, and risk-informed decision-making

Course Lessons

Value You Will Gain

  • Master industry-standard tools including FDS, ANSYS, Python, and machine learning for fire and explosion analysis.
  • Develop practical CFD modelling skills to simulate and evaluate fire and explosion scenarios.
  • Apply AI and data analytics to improve hazard prediction and safety performance.
  • Strengthen risk assessment capabilities through data-driven modelling and validation techniques.
  • Gain hands-on experience with real-world case studies and engineering applications.
  • Enhance your professional capability in fire, process, and industrial safety engineering for research and industry practice.

Who Will Benefit Most

Identify if this programme aligns with your role, goals, and sustainability priorities
  • Fire Safety Engineers and Fire Protection Professionals
  • Process Safety, HSE, and Risk Management Engineers
  • Mechanical, Chemical, and Design Engineers involved in industrial safety
  • Fire and Rescue Personnel responsible for emergency response and incident investigation
  • Consultants, Researchers, and Academics specialising in fire, explosion, or safety engineering
  • Technical Professionals and Graduate Engineers seeking to build expertise in CFD, data analytics, and AI for fire and explosion engineering

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