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Course Outline

Introduction

  • Overview of conversational AI systems.
  • Evolution and components of modern conversational systems.

Designing Advanced Conversational Flows

  • Creating dynamic, context-aware dialogues.
  • Handling complex user intents and entities.
  • Building and testing adaptive conversation scenarios.

Advanced NLP Techniques

  • Pre-training and fine-tuning large language models.
  • Implementing named entity recognition (NER) and sentiment analysis.

Backend Integration and Data Handling

  • Connecting bots to enterprise-level data sources and APIs.
  • Using databases and cloud services for data storage and retrieval.

Adaptive Learning for Conversational AI

  • Implementing user feedback loops and learning mechanisms to improve interactions.
  • Building adaptive learning features and evaluating their performance.

Summary and Next Steps

Requirements

  • Foundational understanding of conversational AI and NLP models.
  • Experience with programming languages such as Python.
  • Basic knowledge of API integration and cloud services.

Audience

  • AI project managers.
  • Conversational AI developers.
  • Senior software engineers.
 14 Hours

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