Live Virtual Hands On Lab: Distributed Training at Scale with Ray and PyTorch

Ready to move beyond single-GPU limits and master distributed systems? Join us for a live virtual hands on lab where ML and platform engineers will explore how to scale model training from a single node to a massive cluster using PyTorch and Ray. In this virtual session you will learn: What is distributed Training ? And do we need it? Introduction to Distributed Data Parallel (DDP) Utilize advanced DDP techniques with ZeRO-1, ZeRO-2, ZeRO-3, and FSDP Introduction to Ray and how you can use Ray Train to train models at scale Training a model at scale using Ray Train and PyTorch at scale This free lab is more than a webinar. You’ll leave with a working understanding of Ray, a reusable project you can build on, and a clear view of how Ray and Anyscale work together to accelerate AI development.

Webinar: Getting Started with Distributed Training at Scale
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Webinar: Getting Started with Distributed Training at Scale

Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray
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Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

Intro to Audio Processing for Deep Learning
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Intro to Audio Processing for Deep Learning

JVM Dev Talks 16/05/2026. Sandu Nicula — Cache Me If You Can  Building Resilient Java Caching Layers
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JVM Dev Talks 16/05/2026. Sandu Nicula — Cache Me If You Can Building Resilient Java Caching Layers

[Full Version] Guest Lecture Series #3 - Introduction to AI Agent Using Agent Development Kit
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[Full Version] Guest Lecture Series #3 - Introduction to AI Agent Using Agent Development Kit

Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan
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Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

Web Scraping Using Python For Beginners and File Handling in Python | Python Web Scraping
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Web Scraping Using Python For Beginners and File Handling in Python | Python Web Scraping

Multimodal data: Architecting pipelines that don’t break at scale
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Multimodal data: Architecting pipelines that don’t break at scale

Distributed Model Training with Ray at Capital One | Ray Summit 2025
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Distributed Model Training with Ray at Capital One | Ray Summit 2025

Brendan Burns: Lessons from Building Kubernetes and the Future of AI Infrastructure
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Brendan Burns: Lessons from Building Kubernetes and the Future of AI Infrastructure

Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker
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Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

Python Variables | Python Operators | Python Tutorial For Beginners | Intellipaat
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Python Variables | Python Operators | Python Tutorial For Beginners | Intellipaat

Quantum Just Killed AI Data Centers
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Quantum Just Killed AI Data Centers

Why Ray Became a Distributed Computing Engine for Modern AI
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Why Ray Became a Distributed Computing Engine for Modern AI

Full Walkthrough: Workflow for AI Coding — Matt Pocock
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Full Walkthrough: Workflow for AI Coding — Matt Pocock

What I Learned From Implementing LLM Architectures From Scratch (And How to Get Started)
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What I Learned From Implementing LLM Architectures From Scratch (And How to Get Started)

Designing Data-intensive Applications with Martin Kleppmann
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Designing Data-intensive Applications with Martin Kleppmann

🔥 GOD UNLEASHES the Truth | Psalms 23, 35, 91 and 112 To Break Curses and Activate Abundance
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🔥 GOD UNLEASHES the Truth | Psalms 23, 35, 91 and 112 To Break Curses and Activate Abundance

Exclusive Interview With Nvidia CEO Jensen Huang (Full Special)
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Exclusive Interview With Nvidia CEO Jensen Huang (Full Special)

Everything We Got Wrong About Research-Plan-Implement -  Dexter Horthy
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Everything We Got Wrong About Research-Plan-Implement - Dexter Horthy