OBJECTIVES: 

∙ To familiarize faculty members with the  fundamentals of Artificial Intelligence and  Machine Learning and their potential  applications in various Civil Engineering  domains. 

∙ To enable participants to apply AI/ML  techniques in solving real-world Civil  Engineering problems such as structural health  monitoring, traffic prediction, material  optimization, and water resource management. 

∙ To demonstrate the use of modern tools and  software platforms (e.g., Python, MATLAB,  Tensor Flow, Scikit-learn) for developing  AI/ML models specific to Civil Engineering  datasets. 

∙ To promote interdisciplinary research by  integrating AI/ML with traditional Civil  Engineering practices to enhance efficiency,  safety, sustainability, and decision-making  processes. 

Theme/Scope: 

This FDP aims to bridge the gap between  traditional Civil Engineering practices and modern  AI/ML technologies. It will cover applications in  structural analysis, construction management,  geotechnical evaluation, environmental monitoring,  and transportation systems. The program will  include hands-on sessions on data-driven  modelling, predictive maintenance, and decision support systems, enabling faculty to incorporate  AI/ML in teaching, research, and consultancy  projects aligned with the evolving needs of smart  and sustainable infrastructure development. 


Important Topics to be covered:

     ∙ To introduce the fundamentals of Artificial  Intelligence (AI) and Machine Learning (ML)  and their relevance in solving real-world Civil Engineering problems. 

∙ To explore practical applications of AI/ML in  Civil Engineering domains such as  Geotechnical analysis, material behavior  modelling, Structural health monitoring,  Traffic prediction, Construction management,  , Climate modelling, Hydraulics and Water  Resources Engineering.  

∙ To equip participants with hands-on  experience using AI/ML tools and techniques  for data analysis, predictive modelling, and  decision-making in Civil Engineering projects. 


Targeted Participants:  

∙ Students/ Research Scholars  

∙ Faculty members 

∙ Industry Professionals 

∙ Target Departments: Civil, Environmental,  Architecture, Chemical, Mining, Mechanical  


Registration Fee (excluding 18% GST) :


Participants             Amount (in INR) 

For offline participants, registration kit, tea and lunch will be provided during training program. Fee is non-refundable. Certificates will be issued to the participants only after attending the complete course.