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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 within the agentic AI landscape
- Core features and competitive advantages
Principles of Agent Design
- Defining the components of an AI agent
- Establishing agent roles, memory structures, and tool sets
- Distinguishing between enterprise-oriented and developer-centric agents
Hands-On Exploration of Mistral Medium 3
- Model initialization and configuration strategies
- Tuning and optimizing inference processes
- Managing multimodal and coding workflows
Development with Devstral
- Designing code-centric agents
- Utilizing Devstral for enhanced code comprehension
- Best practices for engineering assistants
Integration with Le Chat Enterprise
- Implementing Le Chat for enterprise-level agents
- Incorporating RBAC, SSO, and compliance standards
- Linking enterprise applications and data repositories
End-to-End Agent Workflows
- Orchestrating Mistral Medium 3, Devstral, and Le Chat together
- Constructing multi-tool workflows involving connectors, APIs, and data sources
- Applying grounding and RAG patterns
Deployment Strategies and Governance
- Comparing self-hosted solutions versus API deployment
- Implementing monitoring, logging, and observability measures
- Addressing cost, performance, and compliance requirements
Conclusion and Future Directions
Requirements
- Proficiency in Python programming
- Practical experience with machine learning workflows
- Knowledge of API mechanics and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied Machine Learning Teams
- Product Developers
14 Hours
