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 Duration 14 hours

Course Outline

Introduction to Mistral Conversational AI

  • Overview of Mistral conversational models
  • Exploring capabilities and limitations
  • Identifying enterprise use cases for assistants

Utilizing Mistral Connectors

  • Linking to Google Drive, Docs, and Calendars
  • Integrating with various SaaS tools
  • Handling authentication and permission management

Retrieval-Augmented Generation (RAG)

  • Understanding the grounding of conversational assistants
  • Indexing enterprise data sources
  • Querying data and generating context-aware responses

Crafting User Experiences for Assistants

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

Integration and Deployment Strategies

  • Embedding assistants within product workflows
  • Leveraging APIs and SDKs for deployment
  • Establishing testing and iteration cycles

Performance and Monitoring

  • Assessing response quality
  • Implementing logging and analytics
  • Setting up continuous improvement loops

Case Studies and Best Practices

  • Real-world implementation examples
  • Key lessons from enterprise deployments
  • Future trends in conversational assistants

Summary and Next Steps

Requirements

  • Working knowledge of web applications and APIs
  • Background in software integration or full-stack development
  • Basic familiarity with conversational AI or chatbots

Target Audience

  • Product Managers
  • Full-stack Developers
  • Integration Engineers

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