Training 5: Ray Core Deep Dive: API, Architectures and Best Practices (3 hours)

1:00 PM - 4:00 PM
Level: Intermediate to Advanced
Hands-on Lab
ML Engineer, Data Scientist
Ray Core

The deep dive into Ray Core provides you with an extensive and practical understanding of the Ray Core concepts. Throughout the course, you will understand Ray’s architecture, API components (tasks, actors, objects), core services and observability tooling that enable simple scaling of Python and ML applications. During thoughtful discussion, we will share best practices and recommended techniques validated by industry experts.

With this hands-on understanding of Ray Core, you'll be able to apply this knowledge to tackle challenging scaling problems and deliver robust solutions that meet your organization's needs.

Learning Outcomes

  • Apply an in-depth understanding of Ray Core to scale Python applications.
  • Optimize performance and scalability by implementing best practices and recommended techniques to improve existing Ray applications.

Prerequisites

  • Intermediate experience with the Python programming language.
  • Basic knowledge of distributed computing and parallel programming concepts.
  • Basic familiarity with machine learning concepts is helpful, but not required context.
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