AI for Science Curriculum

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Teaching Deep Learning and Physics Informed Neural Network on GPUs

AI for Science and Technology Curriculum

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IIT Delhi and NVIDIA have co-developed the reference AI for Science curriculum covering the academic theory and application of Deep Learning (DL) and Physics Informed Neural Network (PINN) on GPUs using frameworks like NVIDIA Modulus^™.

Simulations are widely used to model a variety of real-world problems rooted in science & engineering domains. While initial developments have involved purely data-driven AI techniques to build the surrogate for simulations, recent efforts have focused on the infusion of scientific laws in the Neural Networks. By incorporating NVIDIA GPUs and delivering AI-driven content through the curriculum, educators can break barriers in advanced teaching and learning.

Benefits for Educators

Removing barriers to teaching new technologies

Advance education for the scientific community by easy to access materials, based on industrial applicable skills.

Empowering educators with easy-to-use reference curriculum will benefit the future by integrating AI for Scientific Domains.

The curriculum developed by leading research institute IIT-Delhi and NVIDIA not only combines the fundamental theory but also the application in Industry using latest GPU architectures.

Teach State-of-The-Art Techniques for Convergence of AI and HPC

Download and leverage this Reference Curriculum in your Institute Today

The ready-to-use courseware, provides instructors with the ability to customize the courses for their respective universities and covers topics including:

Introduction to Deep Learning
Difference between Data Driven vs Physics Informed Approach
Convolution Neural Network
Sequence Learning
Physics Informed Deep Learning ( PINN )
Physics Informed Deep Learning for inverse problems

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FAQs

Under what license is the material published?

The material is published under CC-BY-SA clause.
I am working as a faculty/professor in an institute. Can I use this curriculum as base, modify and use it to offer a course in my institute?

Yes, the idea behind creating a reference curriculum is to promote AI for Science. Please do provide credits to original authors as per the LICENSE part of the package.
I am a student and want to use this material to learn. Can I still download and refer to it?

Yes, the students can also download and learn as most slides and labs are designed to be self-explanatory.
Prerequisites
The curriculum expects the audience to be familiar with Python programming.

Users should have also taken some fundamental course on statistics and linear algebra

The frameworks used for hands-on labs are:

PyTorch

Numpy

Matplotlib

h5py

NVIDIA Modulus

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Teaching Deep Learning and Physics Informed Neural Network on GPUs

Benefits for Educators

Removing barriers to teaching new technologies

Teach State-of-The-Art Techniques for Convergence of AI and HPC

Download and leverage this Reference Curriculum in your Institute Today

FAQs

Under what license is the material published?

I am working as a faculty/professor in an institute. Can I use this curriculum as base, modify and use it to offer a course in my institute?

I am a student and want to use this material to learn. Can I still download and refer to it?

Prerequisites

Register to Download The Reference Curriculum