Course curriculum

    1. Introduction to Ray Serve LLM

    2. What is LLM Serving?

    3. Key Concepts & Optimization

    4. Challenges in LLM Serving

    5. Ray LLM Architecture and Inference

    6. Getting Started with Ray Serve LLM

    7. Key Takeaways

    8. All Resources

    1. Overview

    2. Why Use a Medium-Sized Model?

    3. Setting Up Ray Serve LLM

    4. Local Deployment & Inference

    5. Deploying to Anyscale Services

    6. Advanced Topics: Monitoring & Optimization

    7. Summary & Outlook

    8. All Resources

    1. Overview

    2. Advanced Features Preview

    3. Deploying LoRA Adapters

    4. Getting Structured JSON Output

    5. Setting up Tool Calling

    6. How to Choose an LLM?

    7. Conclusion and Next Steps

    8. All Resources

About this course

  • Free
  • 24 lessons
  • 2 hours of video content

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