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Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models, including Medium 3, Le Chat Enterprise, and Devstral
- Strategic positioning within the agentic AI landscape
- Core features and competitive advantages
Principles of Agent Design
- Defining the fundamental nature of an AI agent
- Establishing agent roles, memory structures, and tool utilization
- Distinguishing between enterprise-oriented and developer-centric agents
Practical Application with Mistral Medium 3
- Initial model setup and configuration
- Techniques for inference tuning and optimization
- Handling multimodal and coding-specific workflows
Development with Devstral
- Designing code-first agent architectures
- Integrating Devstral for advanced code comprehension
- Best practices for engineering assistant functionalities
Integrating Le Chat Enterprise
- Deploying Le Chat to support enterprise agent requirements
- Implementing RBAC, SSO, and compliance protocols
- Linking enterprise applications and data repositories
End-to-End Agent Workflow Construction
- Synthesizing Mistral Medium 3, Devstral, and Le Chat capabilities
- Creating multi-tool workflows involving connectors, APIs, and data sources
- Implementing grounding and RAG (Retrieval-Augmented Generation) patterns
Deployment and Governance Strategies
- Comparing self-hosting versus API-based deployment models
- Establishing monitoring, logging, and observability frameworks
- Addressing cost, performance, and compliance requirements
Conclusion and Forward Path
Requirements
- Solid comprehension of Python programming
- Practical experience with machine learning workflows
- Proficiency in API usage and model integration
Target Audience
- AI engineers
- Solution architects
- Applied machine learning teams
- Product developers
14 Hours
