Announcing a two-part Federated Learning course series, in collaboration with Flower Labs!
Federated learning allows models to be trained across multiple devices or organizations without sharing data, and in this course series, instructed by Flower Labs’ Daniel J. Beutel and Nicholas Lane, you’ll learn to use the Flower framework to build federated learning systems and fine-tune LLMs with private data.
1️⃣ The first course, Intro to Federated Learning, covers the basics of federated training, tuning, data privacy, and bandwidth management.
2️⃣ The second course, Federated Fine-tuning of LLMs with Private Data, focuses on applying federated learning to LLMs, including data memorization and resource requirements, with a focus on efficiency and privacy techniques like PEFT and DP.
Start with the course that matches your knowledge level in federated learning and start today!