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Duration 14 hours
Course Outline
The Mistral AI Ecosystem: An Introduction
- Overview of Mistral models, including Medium 3, Le Chat Enterprise, and Devstral
- Role within the agentic AI landscape
- Defining features and unique advantages
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise and developer-focused agents
Working with Mistral Medium 3
- Model initialization and setup
- Tuning inference for optimal performance
- Handling multimodal and coding tasks
Development with Devstral
- Designing code-centric agents
- Leveraging Devstral for advanced code comprehension
- Best practices for engineering assistants
Integrating Le Chat Enterprise
- Deploying Le Chat for enterprise-level agents
- Implementing RBAC, SSO, and compliance frameworks
- Linking enterprise applications and data repositories
Comprehensive Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat
- Creating multi-tool workflows using connectors, APIs, and data sources
- Applying grounding and RAG patterns
Deployment and Governance
- Comparing self-hosted vs. API-based deployment
- Monitoring, logging, and system observability
- Addressing cost, performance, and compliance factors
Conclusion and Future Steps
Requirements
- Proficiency in Python programming
- Practical experience with machine learning workflows
- Knowledge of APIs and model integration
Target Audience
- AI engineers
- Solution architects
- Applied machine learning teams
- Product developers
