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
Foundations of Mistral Conversational AI
- Introduction to Mistral conversational models
- Key capabilities and inherent limitations
- Strategic use cases for enterprise assistants
Managing Mistral Connectors
- Linking Google Drive, Docs, and Calendars
- Integrating with broader SaaS ecosystems
- Handling authentication and permission management
Implementing Retrieval-Augmented Generation (RAG)
- Grounding conversational logic with RAG concepts
- Creating indices for enterprise data
- Executing context-aware queries and responses
Crafting User Experiences for Assistants
- Core principles of conversational UX design
- Structuring flows for internal utility tools
- Developing polished customer-facing chat experiences
Deployment Strategies
- Embedding assistants seamlessly into product workflows
- Utilizing APIs and SDKs for deployment
- Establishing testing and iterative refinement cycles
Performance Optimization
- Assessing the quality of AI responses
- Implementing logging and analytics tracking
- Building loops for continuous improvement
Insights from Case Studies
- Reviewing real-world implementation examples
- Extracting lessons from enterprise deployments
- Exploring the future trajectory of conversational assistants
Conclusion and Roadmap
Requirements
- A solid grasp of web applications and API architecture
- Practical experience in software integration or full-stack development
- Basic knowledge of conversational AI or chatbot technologies
Target Audience
- Product managers
- Full-stack developers
- Integration engineers
14 Hours