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Course Outline

Introduction to the Mistral AI Ecosystem

  • Survey of Mistral models, including Medium 3, Le Chat Enterprise, and Devstral.
  • Strategic positioning within the agentic AI landscape.
  • Core features and unique differentiators.

Foundations of Agent Design

  • Defining the characteristics of an AI agent.
  • Specifying agent roles, memory structures, and toolsets.
  • Distinguishing between enterprise-focused and developer-centric agents.

Practical Application of Mistral Medium 3

  • Initial model setup and configuration processes.
  • Strategies for inference tuning and optimization.
  • Implementing multimodal and coding-centric workflows.

Developing with Devstral

  • Principles of code-first agent design.
  • Leveraging Devstral for advanced code comprehension.
  • Best practices for engineering assistant integration.

Integrating Le Chat Enterprise

  • Deployment strategies for enterprise-level agents.
  • Incorporating RBAC, SSO, and compliance standards.
  • Linking enterprise applications and data repositories.

Comprehensive Agent Workflows

  • Synergizing Mistral Medium 3, Devstral, and Le Chat.
  • Constructing multi-tool workflows using connectors, APIs, and diverse data sources.
  • Applying grounding and RAG (Retrieval-Augmented Generation) patterns.

Deployment Strategies and Governance

  • Comparing self-hosting options with API-based deployment.
  • Establishing monitoring, logging, and observability frameworks.
  • Navigating considerations related to cost, performance, and compliance.

Wrap-Up and Future Directions

Requirements

  • A solid grasp of Python programming fundamentals.
  • Practical experience with machine learning workflows.
  • Proficiency in API interactions and model integration.

Target Audience

  • AI Engineers.
  • Solution Architects.
  • Applied Machine Learning Teams.
  • Product Developers.
 14 Hours

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