Course Outline

Introduction

  • Overview of Conversational AI Systems for Government
  • Evolution and Components of Modern Conversational Systems for Government

Designing Advanced Conversational Flows for Government

  • Creating Dynamic, Context-Aware Dialogues for Government Applications
  • Handling Complex User Intents and Entities in Government Scenarios
  • Building and Testing Adaptive Conversation Scenarios for Government Use Cases

Advanced NLP Techniques for Government

  • Pre-training and Fine-tuning Large Language Models for Government Applications
  • Implementing Named Entity Recognition (NER) and Sentiment Analysis in Government Contexts

Multilingual and Cross-Language Processing for Government

  • Strategies for Supporting Multiple Languages in a Single Project for Government
  • Integrating and Testing NER and Sentiment Analysis in a Conversational Bot for Government Use

Backend Integration and Data Handling for Government

  • Connecting Bots to Enterprise-Level Data Sources and APIs for Government
  • Using Databases and Cloud Services for Data Storage and Retrieval in Government Projects

Security and Compliance Considerations for Government

  • Ensuring Data Privacy, Encryption, and Secure User Interactions for Government Systems
  • Developing API Connections and Implementing Data Security Protocols for Government Applications

Designing User-Centric Interfaces for Government

  • Enhancing User Experience with Voice and Visual Interactions in Government Services

Adaptive Learning for Conversational AI in Government

  • Implementing User Feedback Loops and Learning Mechanisms to Improve Interactions for Government
  • Building Adaptive Learning Features and Evaluating Their Performance in Government Projects

Managing Conversational AI Projects for Government

  • Agile Project Management Techniques Specific to AI Projects for Government
  • Defining KPIs and Success Metrics for Conversational Projects for Government

Testing and Optimization Strategies for Government

  • Continuous Testing Frameworks for Conversational AI in Government
  • Monitoring, Analytics, and Refining Models Post-Deployment for Government Systems
  • Conducting Performance Tests and Optimization Routines for Government Applications

Summary and Next Steps for Government

Requirements

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

Audience

  • AI project managers for government initiatives
  • Conversational AI developers for government systems
  • Senior software engineers working on government projects
 35 Hours

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