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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 competitive differentiators
Principles of Agent Design
- Defining the components of an AI agent
- Establishing agent roles, memory structures, and tool usage
- Distinguishing between enterprise and developer-centric agents
Hands-On Exploration of Mistral Medium 3
- Model setup and configuration strategies
- Tuning inference for optimal performance
- Managing multimodal and coding workflows
Development with Devstral
- Designing code-first agents
- Integrating Devstral for enhanced code understanding
- Best practices for engineering assistants
Le Chat Enterprise Integration
- Deploying Le Chat for enterprise-level agents
- Implementing RBAC, SSO, and compliance controls
- Connecting enterprise applications and data repositories
End-to-End Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat capabilities
- Constructing multi-tool workflows involving connectors, APIs, and data sources
- Applying grounding and RAG patterns
Deployment and Governance
- Comparing self-hosting with API-based deployment
- Implementing monitoring, logging, and observability
- Balancing cost, performance, and compliance requirements
Conclusion and Future Steps
Requirements
- Proficiency in Python programming
- Experience with machine learning workflows
- Knowledge of APIs and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
