We’re excited to introduce the Anyscale Technical Webinar Series, a new series of webinars designed to help engineers, data scientists, and ML practitioners get hands-on practice with Ray and distributed AI workloads.

Last month, we hosted our first webinar where hundreds of community members went through an introduction to Anyscale and Ray AI libraries. The webinar, Introduction to Anyscale and Ray AI Libraries, is available on demand now.  

Going forward, each webinar will focus on real-world AI use cases and distributed computing challenges. Instructors will walk through technical notebooks, live demos, and interactive Q&A. Whether you’re just getting started with Ray or looking to optimize large-scale workloads, this series will provide practical insights to accelerate your AI and ML projects.

LinkWhat to Expect

Each session in the Anyscale Technical Webinar Series will follow the same structured format:

• 10-minute introduction – Why Ray? Why Anyscale?

• 40-minute technical deep dive – Hands-on notebook walkthrough

• 10-minute live Q&A – Get answers to your questions in real-time

This series runs monthly on the last Wednesday of each month.

LinkUpcoming Webinars

Link1. Introduction to Ray Data: Processing Large Datasets on Heterogeneous Clusters (March 26)

REGISTER HERE!

In this webinar, we’ll cover:

• How Ray Data enables distributed data processing

• Optimizing performance across CPUs and GPUs

• Hands-on session with real-world datasets

Link2. Ray Data: LLMs (April 30)

In this webinar, we’ll cover:

• New APIs in Ray Data optimizing for throughput for batch LLM inference

• Scaling inference pipelines efficiently

• Managing distributed workloads for LLM inference

• Hands-on batch LLM inference example

Link3. Introduction to Ray Train (May 28)

In this webinar, we’ll cover:

• Distributed model training made easy

• Running scalable PyTorch training with Ray Train

• Hands-on notebook session

Link4. Distributed Model Training with Ray Train and XGBoost (June 25)

In this webinar, we’ll cover:

• Training large-scale models with XGBoost on Ray

• Optimizing resource usage for efficiency

• Hands-on notebook session

Link5. Observability for Ray Applications (July 30)

In this webinar, we’ll cover:

• Debugging and monitoring distributed workloads

• Using Ray observability tools for large-scale AI

• Hands-on session with logging, metrics, and dashboards

LinkHow to Register

Registration will be live three weeks before each webinar on the Anyscale events page. Sign up early to secure your spot!

LinkWhy Attend?

• Learn from the experts: Sessions are led by the Anyscale team, the creators of Ray.

• Hands-on learning: Work through live notebooks and get practical experience.

• Engage with the community: Connect with other developers solving distributed computing challenges.

• Exclusive resources: Get access to free e-learning materials, labs, and follow-up content to deepen your knowledge.

LinkStay Connected

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Join us in this technical deep dive into Ray and Anyscale. Whether you're a beginner or an advanced user, there’s something for everyone.