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Course Outline
Introduction
- Overview of Conversational AI systems
- The evolution and key components of modern conversational architectures
Designing Advanced Conversational Flows
- Constructing dynamic, context-aware dialogues
- Managing complex user intents and entities
- Developing and validating 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
- Leveraging databases and cloud services for data storage and retrieval
Adaptive Learning for Conversational AI
- Deploying user feedback loops and learning mechanisms to enhance interactions
- Building adaptive learning features and assessing their performance
Summary and Next Steps
Requirements
- A solid grasp of conversational AI fundamentals and NLP models
- Proficiency in programming languages such as Python
- Foundational knowledge of API integration and cloud-based services
Target Audience
- AI project managers
- Conversational AI developers
- Senior software engineers
14 Hours
