Decentralized AI at Scale with NVIDIA Flare
This hands-on course introduces NVIDIA FLARE for implementing privacy-preserving distributed machine learning at scale. Learners will explore how to deploy federated and decentralized AI systems across multiple organizations while safeguarding data sovereignty and regulatory compliance.
Who Should Take This Course:
Data scientists, AI engineers, and technical leaders interested in building scalable federated learning pipelines. A working knowledge of machine learning is recommended.
What You Will Learn:
• Fundamentals of decentralized and federated learning architectures
• How to set up NVIDIA FLARE clusters and manage client-server workflows
• Techniques for scaling AI across multiple organizations without centralizing data
• Best practices for privacy, security, and compliance in distributed AI systems
Why This Course Matters:
As data privacy regulations and distributed data architectures become the norm, mastering decentralized AI is essential. FLARE enables collaboration across institutions without compromising data control, making this course valuable for anyone deploying AI in regulated or multi-party settings.