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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)
- Role within the agentic AI landscape
- Core features and unique advantages
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise-focused and developer-centric agents
Practical Application with Mistral Medium 3
- Configuring and setting up the model
- Tuning inference for optimal performance
- Handling multimodal and coding tasks
Development with Devstral
- Code-first strategies for agent design
- Utilizing Devstral for deep code analysis
- Best practices for engineering assistants
Integration with Le Chat Enterprise
- Implementing Le Chat for enterprise-level agents
- Setting up RBAC, SSO, and compliance frameworks
- Linking enterprise applications and data repositories
End-to-End Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat
- Constructing multi-tool workflows (connectors, APIs, data sources)
- Implementing grounding and RAG patterns
Deployment and Governance
- Comparing self-hosted solutions vs API-based deployment
- Implementing monitoring, logging, and observability
- Balancing cost, performance, and compliance requirements
Recap and Future Directions
Requirements
- Proficiency in Python programming
- Practical experience with machine learning pipelines
- Knowledge of API mechanics and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
