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Course Outline
Introduction to the Mistral AI Ecosystem
- Review of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Role within the agentic AI landscape
- Primary 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
Practical Work with Mistral Medium 3
- Model initialization and setup
- Adjusting and optimizing inference
- Multimodal and coding task workflows
Development using Devstral
- Code-centric agent architecture
- Incorporating Devstral for code analysis
- Best practices for engineering assistance
Integration with Le Chat Enterprise
- Implementing Le Chat for enterprise-grade agents
- Integrating RBAC, SSO, and compliance protocols
- Linking enterprise applications and data repositories
Comprehensive Agent Workflows
- Synergizing Mistral Medium 3, Devstral, and Le Chat
- Creating multi-tool workflows (connectors, APIs, data feeds)
- Implementing grounding and RAG methodologies
Deployment and Governance
- Choosing between self-hosting and API deployment
- Monitoring, logging, and observability practices
- Evaluating cost, performance, and compliance factors
Recap and Future Directions
Requirements
- A solid grasp of Python programming
- Proficiency in machine learning workflows
- Awareness of API mechanisms and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
14 Hours
