FourthBrain Workshop
LLMOps: The Art of Implementation
Deploy, Monitor and support your LLM App
A 3-week workshop for engineers on the Ops stack for LLM applications. You'll learn to deploy, monitor and support an application including advanced RAG and multi-modal apps.
- Date: . Monday, March 18 - Wednesday, April 3
- Time: 4-7pm PT on Mondays and Wednesdays
- Cost: $2,000 for individuals | $6,000 for teams
Dive deep into the world of LLMs with this intensive three-week workshop. This meticulously designed course bridges the gap between theoretical knowledge and practical application, providing you with hands-on experience in building, evaluating, and scaling LLM applications.
You'll navigate through the complexities of the LLMOps lifecycle, distinguishing it from traditional MLOps. From mastering advanced Retrieval-Augmented Generation (RAG) techniques to deploying multi-modal applications on the cloud, you'll learn to operationalize LLMs at scale, ensuring continuous improvement through effective monitoring and feedback loops.
Key Outcomes
Gain a comprehensive understanding of the LLMOps lifecycle, how it diverges from MLOps, and operationalize multiple LLM apps from start to finish
Learn to construct applications using advanced RAG techniques and establish monitoring and feedback loops for continuous improvement
Construct an evaluation pipeline with best-in-class metrics and learn the intricacies of scaling multi-modal applications as cloud API services
Workshop Schedule
This workshop includes two live sessions a week on Tuesdays and Thursdays, plus additional practice on your own time. You will also have access to Slack to collaborate with your peers and instructors outside of class time.
- What differentiates LLMOps from MLOps
- Master prompt engineering management and experiment tracking
- Enhance LLM generation with RAG and fine-tuning
- Host and deploy an LLM on your own infrastructure
- Review practical techniques for evaluating LLMs, optimizing performance, and fine-tuning for specific tasks
This workshop is for you if:
You are a software, ML, or dev ops engineer looking to expand your knowledge of LLM deployments
You have a foundational understanding of MLOps and wish to extend your expertise into LLMOps
You are eager to learn about the latest advancements in AI applications and how to operationalize these technologies at scale
How to Join
As an Individual
Choose this if you plan to join the workshop on your own and work on a solo project. Register below.
Many employers offer reimbursement for programs like ours. Check out our tips for getting reimbursed.
Register Here
FAQs
