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- Fine-Tune SLMs & Build Multi-Agent NL2SQL Apps with Amazon AgentCore
Fine-Tune SLMs & Build Multi-Agent NL2SQL Apps with Amazon AgentCore
AI
생성형 AI
기계 학습
SageMaker
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대면
Nicolas de Place | Statup Solutions Architect, Thomas Buatois | Statup Solutions Architect
Français
300 - 고급, 400 - 전문가
발표자
Fine-Tune SLMs & Build Multi-Agent NL2SQL Applications with Amazon AgentCore
In this hands-on workshop, you'll fine-tune a Small Language Model (SLM) for NL2SQL tasks and deploy it as part of a multi-agent system using Amazon AgentCore.
What you'll build:
- Fine-tune an SLM on a custom NL2SQL dataset using Amazon SageMaker
- Deploy your fine-tuned model as an agent endpoint
- Build a multi-agent architecture with Amazon AgentCore that orchestrates specialized agents (query generation, validation, execution)
- Chain agents to translate natural language questions into accurate SQL queries
What you'll learn:
- SLM fine-tuning best practices (LoRA, dataset preparation, evaluation)
- NL2SQL patterns and prompt engineering for structured outputs
- Multi-agent orchestration with AgentCore (routing, tool-use, memory)
- Cost and latency optimization vs. large foundation models
Who should attend: ML engineers, AI/ML leads, and technical founders at startups who want to build production-grade agentic applications using fine-tuned small models instead of expensive large LLMs.
Practical info:
📍 Station F, Paris
👥 Limited to 15 participants
💻 Bring your laptop — fully hands-on with AWS-provisioned environments
🗣️ Workshop in French, materials in English