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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
Testimonials (1)
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