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Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Positioning within the agentic AI landscape
- Core features and key differentiators
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise-focused and developer-centric agents
Hands-On with Mistral Medium 3
- Model configuration and initial setup
- Inference tuning and performance optimisation
- Managing multimodal and coding workflows
Building with Devstral
- Code-first approaches to agent design
- Leveraging Devstral for advanced code understanding
- Best practices for engineering assistants
Integrating Le Chat Enterprise
- Deploying Le Chat to support enterprise agent requirements
- Implementing RBAC, SSO, and compliance standards
- Connecting enterprise applications and data repositories
End-to-End Agent Workflows
- Synergising Mistral Medium 3, Devstral, and Le Chat
- Constructing multi-tool workflows using connectors, APIs, and data sources
- Implementing grounding and RAG patterns
Deployment and Governance
- Comparing self-hosting versus API deployment strategies
- Implementing monitoring, logging, and observability
- Addressing cost, performance, and compliance factors
Summary and Recommended Next 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
