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Course Outline
Introduction
- Conversational AI systems overview
- 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
- Fundamental 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
Testimonials (1)
The detail in which the instructor explained all the concepts.
