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Duration 14 hours
Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral).
- Positioning within the agentic AI ecosystem.
- Key features and competitive differentiators.
Principles of Agent Design
- Defining the characteristics of an AI agent.
- Establishing agent roles, memory structures, and tool usage.
- Distinguishing between enterprise-focused and developer-centric agents.
Hands-on Workshop with Mistral Medium 3
- Model setup and configuration.
- Inference tuning and optimization strategies.
- Multimodal and coding workflow integration.
Building Solutions with Devstral
- Code-first approaches to agent design.
- Integrating Devstral for enhanced code understanding.
- Best practices for engineering assistant development.
Le Chat Enterprise Integration
- Deploying Le Chat for enterprise-level agents.
- Implementing RBAC, SSO, and compliance controls.
- Connecting enterprise applications and data stores.
End-to-End Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat.
- Constructing multi-tool workflows involving connectors, APIs, and data sources.
- Implementing grounding and RAG patterns.
Deployment and Governance
- Comparing self-hosting versus API deployment.
- Establishing monitoring, logging, and observability frameworks.
- Addressing cost, performance, and compliance considerations.
Summary and Recommended Next Steps
Requirements
- A solid understanding of Python programming.
- Experience with machine learning workflows.
- Familiarity with APIs and model integration.
Target Audience
- AI Engineers.
- Solution Architects.
- Applied ML Teams.
- Product Developers.
