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Course Outline
Introduction
- Overview of Conversational AI systems.
- The evolution and key components of modern conversational systems.
Designing Advanced Conversational Flows
- Crafting dynamic, context-aware dialogues.
- Managing complex user intents and entities.
- Constructing and validating adaptive conversation scenarios.
Advanced NLP Techniques
- Pre-training and fine-tuning of large language models.
- Application of named entity recognition (NER) and sentiment analysis.
Multilingual and Cross-Language Processing
- Strategies for accommodating multiple languages within a single project.
- Integration and testing of NER and sentiment analysis within conversational bots.
Backend Integration and Data Handling
- Linking bots to enterprise-grade data sources and APIs.
- Utilizing databases and cloud services for data storage and retrieval.
Security and Compliance Considerations
- Safeguarding data privacy, encryption, and secure user interactions.
- Establishing API connections and enforcing data security protocols.
Designing User-Centric Interfaces
- Improving user experience through voice and visual interaction design.
Adaptive Learning for Conversational AI
- Implementing user feedback loops and learning mechanisms to enhance interactions.
- Developing adaptive learning features and assessing their effectiveness.
Managing Conversational AI Projects
- Agile project management techniques tailored to AI projects.
- Defining KPIs and success metrics for conversational initiatives.
Testing and Optimization Strategies
- Continuous testing frameworks for conversational AI.
- Post-deployment monitoring, analytics, and model refinement.
- Execution of performance tests and optimization routines.
Summary and Next Steps
Requirements
- Solid foundational knowledge of conversational AI and NLP models.
- Proficiency in programming languages such as Python.
- Basic understanding of API integration and cloud-based services.
Target Audience
- AI project managers.
- Conversational AI developers.
- Senior software engineers.
35 Hours
