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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 landscape
- Key features and differentiators
Principles of Agent Design
- Defining the components of an AI agent
- Structuring agent roles, memory, and tools
- Distinguishing between enterprise and developer-centric agents
Hands-On with Mistral Medium 3
- Model setup and configuration
- Inference tuning and optimization
- Multimodal and coding workflows
Building with Devstral
- Code-first agent design
- Integrating Devstral for code comprehension
- Best practices for engineering assistants
Le Chat Enterprise Integration
- Deploying Le Chat for enterprise agents
- Implementing RBAC, SSO, and compliance controls
- Connecting enterprise applications and data stores
End-to-End Agent Workflows
- Combining Mistral Medium 3, Devstral, and Le Chat
- Creating multi-tool workflows (connectors, APIs, data sources)
- Grounding and RAG patterns
Deployment and Governance
- Comparing self-hosting versus API deployment
- Monitoring, logging, and observability
- Considerations for cost, performance, and compliance
Summary and Next Steps
Requirements
- Familiarity with Python programming
- Experience with machine learning workflows
- Knowledge of APIs and model integration
Audience
- AI engineers
- Solution architects
- Applied ML teams
- Product developers
