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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 key differentiators
Principles of Agent Design
- Defining the essence of an AI agent
- Establishing agent roles, memory mechanisms, and toolsets
- Distinguishing between enterprise and developer-centric agents
Hands-on Experience with Mistral Medium 3
- Model setup and configuration processes
- Optimizing inference tuning and performance
- Navigating multimodal and coding workflows
Developing with Devstral
- Code-first approaches to agent design
- Leveraging Devstral for enhanced code understanding
- Best practices for engineering assistants
Integrating Le Chat Enterprise
- Deploying Le Chat for enterprise-grade agents
- Implementing 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)
- Applying grounding and RAG patterns
Deployment and Governance
- Evaluating self-hosting versus API deployment
- Establishing monitoring, logging, and observability
- Addressing cost, performance, and compliance factors
Summary and Future Steps
Requirements
- Proficiency in Python programming
- Practical experience with machine learning workflows
- Working knowledge of APIs and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
14 Hours
