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Course Outline
Introduction
- Overview of Conversational AI systems
- The evolution and core components of modern conversational systems
Designing Advanced Conversational Flows
- Crafting dynamic, context-aware dialogues
- Managing complex user intents and entities
- Constructing and testing adaptive conversation scenarios
Advanced NLP Techniques
- Pre-training and fine-tuning large language models
- Applying named entity recognition (NER) and sentiment analysis
Backend Integration and Data Handling
- Linking bots to enterprise-level data sources and APIs
- Utilizing databases and cloud services for robust data storage and retrieval
Adaptive Learning for Conversational AI
- Establishing user feedback loops and learning mechanisms to enhance interactions
- Developing adaptive learning features and assessing their performance
Summary and Next Steps
Requirements
- A solid foundational understanding of conversational AI and NLP models
- Proficiency in programming languages such as Python
- Foundational knowledge of API integration and cloud service architectures
Intended Audience
- AI Project Managers
- Conversational AI Developers
- Senior Software Engineers
14 Hours
