Course Name: Machine Learning and Scientific Computing for Civil Engineers

Faculty Name: Dr. Biswarup Bhattacharyya

Course Period: 5 ^th Jan to 30 ^th Apr 2026 (Tuesday 02:30 PM to 04:00 PM; Friday 04:00 PM to 05:30 PM)

Number of Credits: 3 credits

Prerequisite: Basics of Linear Algebra, Engineering Mathematics

Course Contents:

• Introduction to the course
• Review of probability theory
• Introduction to uncertainty quantification (UQ)
• Monte Carlo simulation (MCS) for UQ
• Theory of Bayesian inference
• Supervised machine learning: Polynomial chaos expansion
• Supervised machine learning: Gaussian process
• Unsupervised learning: Clustering
• Unsupervised learning: Model order reduction
• Neural networks and deep neural networks

What you'll learn: Students will learn about the basic and advanced machine learning approaches along with applications for a variety of engineering problems.

Fee: Rs. 15,000/- Plus GST

Apply here: Registration closed

About the Instructor: Dr. Biswarup Bhattacharyya is a faculty of the Stochastic Computational Modeling (SCM) Lab in the Department of Civil Engineering at IIT Hyderabad. His research areas are uncertainty quantification, physics-informed machine learning for engineering problems, digital twin, etc. He has extensive research experience from France, Switzerland and the US. The proposed course is the outcome of his research work, and it will be particularly interesting for engineering students looking to delve into machine learning.

Instructor Profile

Course Assessment:

Assessment may consist of assignments and/or quizzes and/or viva and/or exams.