Foundations of LLMOps
Get started with LLMOps! Learn how to deploy, monitor, and scale large language models (LLMs) effectively in production. Build the skills to manage LLM lifecycles with confidence.
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Contact our teamWhat will you learn?
In this course, you will explore the foundational aspects of LLMOps, the framework for managing the operational lifecycle of large language models (LLMs). You will learn how to deploy LLMs using best practices, monitor their performance to ensure reliability, and scale infrastructure to meet demands. With hands-on labs, you will set up basic LLMOps pipelines using tools like Docker, Kubernetes, TensorFlow Serving, and MLflow. By the end, you will have the confidence to manage LLMs in production, ensuring they run efficiently and deliver value at scale.
Key takeaways
- Understand the foundations of LLMOps
- Deploy LLMs using best practices
- Monitor LLMs for stability and reliability
- Scale LLM systems to meet demands
- Build pipelines with hands-on labs
Program
- Introduction to LLMOps: Learn the basics of operationalizing large language models.
- Deploying LLMs: Discover best practices and tools for deployment in production.
- Monitoring LLM Performance: Ensure stability and performance through effective monitoring.
- Scaling LLM Systems: Develop techniques for scaling LLM infrastructure efficiently.
- Hands-on Labs: Set up and practice with LLMOps pipelines.
Who is it for?
This training is for developers, data scientists, and AI engineers eager to understand and implement LLMOps. Whether you are new to managing AI models or looking to upskill for production environments, this course is perfect for you.
Requirements
Basic knowledge of the topic is beneficial.
Why should I do this training?
Practical experience
Build pipelines with hands-on labs.
Industry-relevant skills
Learn tools used in real-world LLMOps workflows.
Future-ready expertise
Master LLMs for production environments.
What does it look like?
What else
should I know?
After registering, you will receive a confirmation email with practical information.
See you soon!
Course information
Available remotely or in-person
Duration: 12-14 hours
Hands-on exercises with real repositories
Interactive, project-based learning
Perfect for beginners in LLMOps
Certification awarded upon completion
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