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Course Outline
Fundamentals of the Mistral AI Ecosystem
- Brief introduction to Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Strategic positioning within the agentic AI landscape
- Core features and unique value propositions
Foundations 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 of Mistral Medium 3
- Configuration and initial setup of the model
- Refining inference processes and performance tuning
- Managing multimodal and coding-centric workflows
Development with Devstral
- Approaching agent design with a code-first methodology
- Utilizing Devstral to enhance code comprehension
- Best practices for engineering assistant integrations
Integrating Le Chat Enterprise
- Implementation of Le Chat for enterprise-level agents
- Establishing RBAC, SSO, and compliance frameworks
- Linking enterprise applications and data repositories
Comprehensive Agent Workflows
- Synergizing Mistral Medium 3, Devstral, and Le Chat
- Creating multi-tool workflows involving connectors, APIs, and diverse data sources
- Applying grounding techniques and RAG patterns
Deployment Strategies and Governance
- Comparing self-hosting options versus API-based deployment
- Implementing monitoring, logging, and observability standards
- Evaluating cost, performance, and compliance factors
Concluding Remarks and Future Directions
Requirements
- Proficiency in Python programming
- Practical experience with machine learning workflows
- Knowledge of APIs and model integration processes
Intended Audience
- AI engineers
- Solution architects
- Applied ML teams
- Product developers
14 Hours
