Course Outline
Introduction to Mistral AI Ecosystem
- Overview of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Positioning in the agentic AI ecosystem
- Key features and differentiators
Agent Design Principles
- What makes an AI agent
- Defining agent roles, memory, and tools
- Enterprise vs developer-centric agents
Hands-On with Mistral Medium 3
- Model setup and configuration
- Inference tuning and optimization
- Multimodal and coding workflows
Building with Devstral
- Code-first agent design
- Integrating Devstral for code understanding
- Engineering assistant best practices
Le Chat Enterprise Integration
- Deploying Le Chat for enterprise agents
- RBAC, SSO, and compliance integration
- Connecting enterprise apps and data stores
End-to-End Agent Workflows
- Combining Mistral Medium 3, Devstral, and Le Chat
- Building multi-tool workflows (connectors, APIs, data sources)
- Grounding and RAG patterns
Deployment and Governance
- Self-hosting vs API deployment
- Monitoring, logging, and observability
- Cost, performance, and compliance considerations
Summary and Next Steps
Requirements
- An understanding of Python programming
- Experience with machine learning workflows
- Familiarity with APIs and model integration
Audience
- AI engineers
- Solution architects
- Applied ML teams
- Product developers
Delivery Options
Private Group Training
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- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
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