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 Duration 14 hours

Course Outline

Foundations of Mistral Conversational AI

  • Overview of Mistral's conversational models
  • Key capabilities and inherent limitations
  • Enterprise use cases for AI assistants

Leveraging Mistral Connectors

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

Retrieval-Augmented Generation (RAG) in Practice

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

Crafting User Experiences for Assistants

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

Integration and Deployment Strategies

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

Performance Optimization and Monitoring

  • Assessing response quality and accuracy
  • Implementing logging and analytics
  • Establishing continuous improvement loops

Case Studies and Industry Best Practices

  • Insights from real-world implementations
  • Key lessons from enterprise deployments
  • Emerging trends in conversational assistants

Recap and Road Ahead

Requirements

  • A solid grasp of web applications and API mechanics
  • Prior experience in software integration or full-stack development
  • Broad familiarity with conversational AI systems or chatbots

Target Audience

  • Product managers
  • Full-stack developers
  • Integration engineers

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