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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)
- Strategic positioning within the agentic AI landscape
- Core features and unique value propositions
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
Practical Application with Mistral Medium 3
- Model initialization and configuration
- Tuning inference for optimal performance
- Handling multimodal and coding tasks
Development with Devstral
- Code-centric agent architecture
- Utilizing Devstral for advanced code comprehension
- Best practices for engineering assistants
Integrating Le Chat Enterprise
- Implementing Le Chat for enterprise-level agents
- Incorporating RBAC, SSO, and compliance protocols
- Linking enterprise applications and data repositories
End-to-End Agent Workflows
- Synergizing Mistral Medium 3, Devstral, and Le Chat
- Creating multi-tool workflows utilizing connectors, APIs, and data sources
- Implementing grounding and RAG strategies
Deployment and Governance
- Comparing self-hosting with API-based deployment
- Implementing monitoring, logging, and observability
- Addressing cost, performance, and compliance factors
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
