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 Duration 14 hours

Course Outline

Getting Started with Mistral Conversational AI

  • Introduction to Mistral’s conversational models
  • Key capabilities and inherent limitations
  • Enterprise use cases for AI assistants

Leveraging Mistral Connectors

  • Integration with Google Drive, Docs, and Calendars
  • Connecting with various SaaS tools
  • Handling authentication and permission management

Retrieval-Augmented Generation (RAG)

  • Understanding how to ground conversational assistants
  • Indexing enterprise data effectively
  • Contextual querying and response generation

Crafting Assistant User Experiences

  • Core principles of conversational UX
  • Designing workflows for internal tools
  • Creating engaging customer-facing chat experiences

Integration and Deployment Strategies

  • Embedding assistants into existing product workflows
  • Utilizing APIs and SDKs for deployment
  • Establishing testing and iteration cycles

Performance Optimization and Monitoring

  • Assessing response quality
  • Implementing logging and analytics
  • Fostering continuous improvement loops

Case Studies and Industry Best Practices

  • Insights from real-world implementations
  • Key takeaways from enterprise deployments
  • Future trends in conversational assistants

Conclusion and Future Actions

Requirements

  • Knowledge of web applications and API structures
  • Background in software integration or full-stack development
  • Basic understanding of conversational AI or chatbot technology

Target Audience

  • Product managers
  • Full-stack developers
  • Integration engineers

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