25.8.20
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TrAC Mastering PyTorch

Kimia Safari-Shad

The Mastering PyTorch digital badge is designed to provide a basic understanding of the open-source framework for AI covering Tensors computations, custom architectures, and advanced functions in PyTorch and is offered as a 4-week asynchronous online course. The Mastering PyTorch course is offered by Iowa State University's Translational AI Center (TrAC) and is part of a larger Foundations of AI pathway program.

Skills / Knowledge

  • Machine Learning
  • Tensors Computations
  • Debugging
  • Python
  • Neural Network
  • PyTorch

Issued on

April 3, 2025

Expires on

Does not expire

Earning Criteria

Required

course

The Mastering PyTorch Badge is earned after successful completion of a 4-week, asynchronous, self-paced online course consisting of 3 modules. The 3 modules cover essential topics such as Tensors computations, custom architectures, advanced functions in PyTorch and building and debugging PyTorch codes.

This course offers a blend of hands-on activities, assignments, video lectures and tutorials.

Learning Outcomes:

  • Apply PyTorch Fundamentals in Deep Learning and Scientific Computing

  • Demonstrate Proficiency in Debugging PyTorch codes

  • Develop custom PyTorch layers or functions to address specific tasks

  • List Advanced Functionality in PyTorch

  • Apply PyTorch to solve real-world problems in domains like computer vision and natural language processing

Assessment:

Participants will be assessed on:

  • Engagement with each module

  • Two Coding exercises that include implementing python codes
    based on hands-on activities. This would include coding a custom neural network
    architecture and exploring some additional exercises

  • 2 Quizzes centered on debugging code errors

About TrAC
The Translational AI Center will break down disciplinary silos to bring together core Iowa State artificial intelligence researchers and subject matter experts interested in applying new technologies to their work. The center will initially focus on conducting core artificial intelligence research, as well as pursuing five application areas of artificial intelligence:

  • Materials design and manufacturing

  • Biology, healthcare, and quality of life

  • Autonomy, intelligent transportation, and smart infrastructure

  • Food, energy, and water

  • Ethics, fairness, and adoption.

In addition to serving as a scientific hub for translational artificial intelligence, the center will organize research seminars, host workshops, training, and onboarding programs, offer seed funding for research projects, and serve as an intermediary between private industry partners seeking research services and appropriate university faculty.

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