Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Fundamentals of the Mistral AI Ecosystem
- Survey of Mistral models (Medium 3, Le Chat Enterprise, Devstral)
- Strategic positioning within the agentic AI landscape
- Distinctive features and competitive advantages
Principles of Agent Design
- Core characteristics of an AI agent
- Defining agent responsibilities, memory structures, and toolsets
- Differentiating enterprise-focused agents from developer-centric ones
Practical Application with Mistral Medium 3
- Model initialization and setup
- Inference adjustment and performance enhancement
- Handling multimodal and coding-centric processes
Development with Devstral
- Code-centric agent architecture
- Utilizing Devstral for code analysis and comprehension
- Best practices for engineering assistant tools
Integration of Le Chat Enterprise
- Rolling out Le Chat for enterprise-grade agents
- Implementing RBAC, SSO, and regulatory compliance frameworks
- Linking enterprise applications and data repositories
Comprehensive Agent Workflows
- Orchestrating Mistral Medium 3, Devstral, and Le Chat
- Constructing multi-tool pipelines using connectors, APIs, and data feeds
- Applying grounding techniques and RAG patterns
Deployment and Governance Strategies
- Comparing self-hosted solutions versus API-based deployments
- Establishing monitoring, logging, and observability metrics
- Addressing cost, performance, and compliance requirements
Recap and Future Directions
Requirements
- Proficiency in Python programming
- Practical experience with machine learning pipelines
- Working knowledge of APIs and model integration strategies
Target Audience
- AI Engineers
- Solution Architects
- Applied ML Teams
- Product Developers
14 Hours
