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Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models, including Medium 3, Le Chat Enterprise, and Devstral.
- Role and positioning within the agentic AI landscape.
- Essential features and competitive advantages.
Principles of Agent Design
- Defining the core components of an AI agent.
- Establishing agent roles, memory structures, and tool utilization.
- Distinguishing between enterprise-focused and developer-centric agents.
Practical Application with Mistral Medium 3
- Model setup and configuration processes.
- Tuning inference for optimal performance.
- Exploring multimodal and coding workflows.
Development with Devstral
- Code-first approaches to agent design.
- Incorporating Devstral for enhanced code comprehension.
- Best practices for engineering assistance.
Integrating Le Chat Enterprise
- Deploying Le Chat for enterprise-level agent solutions.
- Implementing RBAC, SSO, and compliance controls.
- Linking enterprise applications and data repositories.
Comprehensive Agent Workflows
- Combining Mistral Medium 3, Devstral, and Le Chat for unified solutions.
- Creating multi-tool workflows involving connectors, APIs, and data sources.
- Applying grounding and RAG patterns effectively.
Deployment and Governance
- Choosing between self-hosting and API deployment models.
- Implementing monitoring, logging, and observability measures.
- Addressing cost efficiency, performance, and compliance requirements.
Conclusion and Future Directions
Requirements
- A solid grasp of Python programming.
- Practical experience with machine learning workflows.
- Proficiency in API interactions and model integration.
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
14 Hours