Course Outline

Introduction

  • Overview of conversational AI systems for government
  • Evolution and components of modern conversational systems for government

Designing Advanced Conversational Flows

  • Creating dynamic, context-aware dialogues for government use
  • Managing complex user intents and entities in a governmental setting
  • Building and testing adaptive conversation scenarios to meet public sector needs

Advanced NLP Techniques

  • Pre-training and fine-tuning large language models for government applications
  • Implementing named entity recognition (NER) and sentiment analysis for government data

Backend Integration and Data Handling

  • Connecting bots to enterprise-level data sources and APIs for government operations
  • Utilizing databases and cloud services for secure data storage and retrieval in the public sector

Adaptive Learning for Conversational AI

  • Implementing user feedback loops and learning mechanisms to enhance interactions for government users
  • Developing adaptive learning features and evaluating their performance within governmental workflows

Summary and Next Steps

Requirements

  • A foundational understanding of conversational artificial intelligence (AI) and natural language processing (NLP) models
  • Experience with programming languages such as Python
  • Basic knowledge of API integration and cloud services for government applications

Audience

  • AI project managers for government initiatives
  • Conversational AI developers for government projects
  • Senior software engineers in the public sector
 14 Hours

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