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Course Outline
Introduction to the Mistral AI Ecosystem
- Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Role within the agentic AI landscape
- Core features and competitive advantages
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing enterprise-oriented versus developer-centric agents
Practical Application with Mistral Medium 3
- Model configuration and setup
- Inference tuning and performance optimisation
- Multimodal and coding workflows
Development with Devstral
- Code-first agent architecture
- Utilising Devstral for code comprehension
- Best practices for engineering assistants
Le Chat Enterprise Integration
- Deploying Le Chat for enterprise-level agents
- Integration of RBAC, SSO, and compliance frameworks
- Linking enterprise applications and data repositories
Comprehensive Agent Workflows
- Combining Mistral Medium 3, Devstral, and Le Chat
- Constructing multi-tool workflows (connectors, APIs, data sources)
- Grounding techniques and RAG patterns
Deployment and Governance
- Self-hosting compared to API deployment
- Monitoring, logging, and observability strategies
- Considerations for cost, performance, and compliance
Summary and Future Steps
Requirements
- A solid understanding of Python programming
- Practical experience with machine learning workflows
- Proficiency with APIs and model integration
Target Audience
- AI engineers
- Solution architects
- Applied ML teams
- Product developers
14 Hours
