Teaching Deep Learning and Physics Informed Neural Network on GPUs

AI for Science and Technology Curriculum

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

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

educators deep learning institute

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

Curriculum demo topics

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

ai for science curriculum

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


Register to Download The Reference Curriculum

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