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 Duration 14 hours

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
  • Key features and unique differentiators

Principles of Agent Design

  • Fundamentals of what constitutes an AI agent
  • Defining agent roles, memory structures, and toolsets
  • Distinguishing between enterprise-focused and developer-centric agents

Hands-On Experience with Mistral Medium 3

  • Model setup and configuration processes
  • Tuning and optimizing inference performance
  • Exploring multimodal and coding workflows

Development with Devstral

  • Designing code-first agents
  • Integrating Devstral for enhanced code understanding
  • Best practices for engineering assistants

Le Chat Enterprise Integration

  • Deploying Le Chat for enterprise-level agents
  • Incorporating RBAC, SSO, and compliance frameworks
  • Linking enterprise applications and data repositories

End-to-End Agent Workflows

  • Combining Mistral Medium 3, Devstral, and Le Chat capabilities
  • 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
  • Monitoring, logging, and observability practices
  • Considerations for cost, performance, and regulatory compliance

Summary and Future Directions

Requirements

  • A solid grasp of Python programming
  • Practical experience with machine learning workflows
  • Knowledge of APIs and model integration processes

Target Audience

  • AI engineers
  • Solution architects
  • Applied ML teams
  • Product developers

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