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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 within the agentic AI landscape
- Distinct features and competitive advantages
Principles of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise-focused and developer-centric agents
Practical Application with Mistral Medium 3
- Setting up and configuring the model
- Adjusting inference parameters for optimization
- Handling multimodal and coding workflows
Development with Devstral
- Designing code-first agents
- Integrating Devstral for code comprehension tasks
- Best practices for engineering assistants
Le Chat Enterprise Integration
- Implementing Le Chat for enterprise-level agents
- Integrating RBAC, SSO, and compliance frameworks
- Linking enterprise applications and data repositories
End-to-End Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat capabilities
- Constructing multi-tool workflows involving connectors, APIs, and diverse data sources
- Implementing grounding and RAG patterns
Deployment and Governance
- Comparing self-hosting versus API-based deployment
- Implementing monitoring, logging, and observability measures
- Evaluating costs, performance, and compliance requirements
Recap and Future Steps
Requirements
- Proficiency in Python programming
- Practical experience with machine learning pipelines
- Knowledge of API management and model integration
Target Audience
- AI engineers
- Solution architects
- Applied machine learning teams
- Product developers
