Course Outline

Introduction to the Mistral AI Ecosystem for Government

  • Overview of Mistral Models (Medium 3, Le Chat Enterprise, Devstral)
  • Positioning within the Agentic AI Ecosystem for Government
  • Key Features and Differentiators for Government Applications

Agent Design Principles for Government

  • Defining What Constitutes an AI Agent in a Government Context
  • Establishing Roles, Memory, and Tools for Government Agents
  • Distinguishing Between Enterprise and Developer-Centric Agents for Government Use

Hands-On with Mistral Medium 3 for Government

  • Model Setup and Configuration for Government Systems
  • Inference Tuning and Optimization for Government Operations
  • Multimodal and Coding Workflows for Government Applications

Building with Devstral for Government

  • Code-First Agent Design for Government Projects
  • Integrating Devstral for Enhanced Code Understanding in Government Environments
  • Best Practices for Engineering Assistants in Government Settings

Le Chat Enterprise Integration for Government

  • Deploying Le Chat for Enterprise Agents in Government Agencies
  • Implementing Role-Based Access Control (RBAC), Single Sign-On (SSO), and Compliance Integration for Government
  • Connecting to Government Enterprise Applications and Data Stores

End-to-End Agent Workflows for Government

  • Combining Mistral Medium 3, Devstral, and Le Chat for Comprehensive Government Solutions
  • Building Multi-Tool Workflows with Connectors, APIs, and Data Sources for Government Use
  • Applying Grounding and Retrieval-Augmented Generation (RAG) Patterns in Government Contexts

Deployment and Governance for Government

  • Evaluating Self-Hosting Versus API Deployment Options for Government Agencies
  • Implementing Monitoring, Logging, and Observability for Government Systems
  • Considering Cost, Performance, and Compliance in Government Deployments

Summary and Next Steps for Government

Requirements

  • An understanding of Python programming for government applications
  • Experience with machine learning workflows in public sector projects
  • Familiarity with APIs and model integration within governmental systems

Audience

  • AI engineers for government initiatives
  • Solution architects for government agencies
  • Applied ML teams in public sector organizations
  • Product developers working on governmental projects
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories