Course Catalogue.

After participating in this course, you will be able to:

• Understand different types of data and apply suitable data processing and analysis
• Learn different types of machine learning methods and their application in civil engineering
• Familiarize with various machine learning algorithms applicable to civil engineering
• Apply various indicators to evaluate the performance of different models
• Employ advanced techniques for data augmentation
• Develop efficient machine-learning solutions for specific civil engineering problems

Description
This three-day course lies at the intersection of Artificial Intelligence and Civil Engineering and aims to equip participants with essential AI skills applicable to civil engineering. Participants will gain a foundational understanding of various types of data in civil engineering, along with proper data processing and visualization techniques.

The course also covers a wide range of supervised, unsupervised, and semi-supervised learning algorithms and their applications in civil engineering. Additionally, participants will learn how to evaluate the performance of models using suitable metrics and indicators. The course emphasizes the importance of explainability and interpretability in machine learning, along with uncertainty quantification using probabilistic approaches. The course offers a practical introduction to Python coding for machine learning and hands-on civil engineering projects in different civil engineering disciplines, such as concrete mixture design, structural analysis and design, and geotechnical analysis.

Case studies and observations of real-world problems will enhance the learning process, and participants will have the opportunity to discuss real cases they have been exposed to in their professional practice.

Who Should Attend
Designers, Construction and Structural Engineers • Project Managers • Technicians and Technologists • Engineers in Training • Construction Inspectors • Inspection Officials • Facility Managers • Architects