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Course Outline
Introduction
- Overview of conversational AI systems for government use
- Evolution and key components of modern conversational systems for government applications
Designing Advanced Conversational Flows
- Creating dynamic, context-aware dialogues to enhance user interactions for government services
- Handling complex user intents and entities in government-related scenarios
- Building and testing adaptive conversation scenarios tailored to 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 in government contexts
Multilingual and Cross-Language Processing
- Strategies for supporting multiple languages in a single project for government operations
- Integrating and testing NER and sentiment analysis in conversational bots for diverse public sector audiences
Backend Integration and Data Handling
- Connecting conversational AI systems to enterprise-level data sources and APIs for government use
- Utilizing databases and cloud services for efficient data storage and retrieval in government applications
Security and Compliance Considerations
- Ensuring data privacy, encryption, and secure user interactions in government conversational AI systems
- Developing API connections and implementing robust data security protocols for government projects
Designing User-Centric Interfaces
- Enhancing the user experience with voice and visual interactions in government services
Adaptive Learning for Conversational AI
- Implementing user feedback loops and learning mechanisms to improve interactions in government applications
- Building adaptive learning features and evaluating their performance in public sector projects
Managing Conversational AI Projects
- Agile project management techniques specific to AI initiatives for government
- Defining key performance indicators (KPIs) and success metrics for conversational AI projects in the public sector
Testing and Optimization Strategies
- Continuous testing frameworks for conversational AI systems in government applications
- Monitoring, analytics, and refining models post-deployment for government use
- Conducting performance tests and optimization routines to ensure optimal public sector service delivery
Summary and Next Steps
Requirements
- A fundamental 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
- Conversational AI developers
- Senior software engineers
35 Hours
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