Get in Touch

Course Outline

Introduction to the Mistral AI Ecosystem

  • Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral).
  • Positioning within the agentic AI ecosystem.
  • Key features and differentiators.

Principles of Agent Design

  • Characteristics that define an AI agent.
  • Defining agent roles, memory, and tools.
  • Distinguishing between enterprise and developer-centric agents.

Practical Application with Mistral Medium 3

  • Model setup and configuration.
  • Inference tuning and optimization.
  • Working with multimodal and coding workflows.

Developing with Devstral

  • Code-first agent design approaches.
  • Integrating Devstral for code understanding.
  • Best practices for engineering assistants.

Integrating Le Chat Enterprise

  • Deploying Le Chat for enterprise agents.
  • Implementing RBAC, SSO, and compliance integration.
  • Connecting enterprise applications and data stores.

End-to-End Agent Workflows

  • Combining Mistral Medium 3, Devstral, and Le Chat.
  • Building multi-tool workflows (connectors, APIs, data sources).
  • Implementing grounding and RAG patterns.

Deployment and Governance

  • Comparing self-hosting versus API deployment.
  • Monitoring, logging, and observability.
  • Addressing cost, performance, and compliance considerations.

Summary and Next Steps

Requirements

  • Proficiency in Python programming.
  • Experience with machine learning workflows.
  • Familiarity with APIs and model integration.

Audience

  • AI engineers.
  • Solution architects.
  • Applied machine learning teams.
  • Product developers.
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories