The LLM Fine-Tuning Masterclass on AWS is a 3-hour session that focuses on fine-tuning large language models (LLMs) using Amazon SageMaker and Amazon Bedrock, a fully managed machine learning service on AWS. The masterclass will cover the full lifecycle of LLM fine-tuning, from data preparation to model deployment, leveraging SageMaker's comprehensive set of tools and services.

The need for this session arises from the increasing adoption of LLMs in various domains and the importance of adapting these models to specific use cases through fine-tuning. By attending this masterclass, participants will learn how to effectively fine-tune LLMs on AWS to ensure high precision, relevance, and reliability in their AI applications.

Agenda:
- Overview of LLMs and fine-tuning
- Amazon SageMaker
- Fine-tuning, Model Evaluation and Iterations
- Deployment and Inferencing fine-tuned LLMs

Who should attend:
- Data Scientists
- ML/AI Developers
- Engineering Managers, CTOs

Key Takeaways:
- Understanding the fundamentals of LLM fine-tuning
- Hands-on experience with fine-tuning LLMs using Amazon SageMaker
- Strategies for optimizing model performance and efficiency
- Best practices for deploying fine-tuned LLMs in production

Prerequisites:
- Familiarity with machine learning and LLM concepts
- Experience with Python programming and popular ML libraries (e.g., TensorFlow, PyTorch)
- Basic understanding of AWS services and infrastructure
- Laptop with a web browser to follow along
- On the day of the workshop, please bring email registration confirmation for entry

Important: Sessions are focused on providing best practices, details of service features and demos for working professionals only. Attendance is subject to AWS Event Terms and Conditions.