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Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Strategic positioning within the agentic AI landscape
- Core features and competitive advantages
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise and developer-centric agents
Practical Application of Mistral Medium 3
- Model configuration and setup
- Tuning inference processes for optimal performance
- Managing multimodal and coding workflows
Building Solutions with Devstral
- Designing code-first agents
- Leveraging Devstral for advanced code comprehension
- Best practices for engineering assistants
Integration with Le Chat Enterprise
- Deploying Le Chat for enterprise-level agents
- Implementing RBAC, SSO, and compliance controls
- Linking enterprise applications and data repositories
End-to-End Agent Workflows
- Synergizing Mistral Medium 3, Devstral, and Le Chat
- Constructing multi-tool workflows using connectors, APIs, and data sources
- Applying grounding and RAG patterns
Deployment and Governance
- Evaluating self-hosting versus API deployment strategies
- Establishing monitoring, logging, and observability frameworks
- Addressing cost, performance, and compliance considerations
Summary and Future Directions
Requirements
- Solid proficiency in Python programming
- Practical experience with machine learning workflows
- Knowledge of APIs and model integration techniques
Target Audience
- AI engineers
- Solution architects
- Applied machine learning teams
- Product developers
14 Hours
