MATRIX AI Scholar: Neuro-Inspired AI for the Edge
Issued by
University of Texas at San Antonio
This badge recognizes successful completion of the NSF AI Spring School, a 3-day program on advancements in artificial intelligence (AI) and machine learning (ML) for edge systems. Participants engage in sessions on energy-efficient and robust AI/ML solutions for edge applications, equipping attendees with valuable skills to address modern AI/ML challenges. Introductory knowledge of AI/ML and Python is helpful but not required.
- Type Learning
- Level Intermediate
- Time Days
- Cost Free
Skills
Earning Criteria
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To earn the badge, attendees must attend at least 80% of the Spring School sessions.
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To earn this badge, attendees must also complete and submit the NSF AI Spring School reflection and feedback form via Qualtrics (link provided to participants).
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Aligned with the annual theme, participants will build foundational understanding and working knowledge of: 1) Challenges in designing, implementing, and deploying AI/ML solutions for edge systems, including energy efficiency, robustness, and security; 2) Advanced techniques such as neuro-inspired AI/ML models (e.g., Spiking Neural Networks) and Federated Learning; 3) Practical skills using Python tools like SNNTorch to model and implement innovative AI/ML solutions.