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Course Outline
Introduction to Large Language Models (LLMs)
- Overview of AI in customer support
- Fundamentals of LLMs
- Evolution of chatbots: from simple scripts to AI-driven support
Architecture of LLMs
- Understanding the building blocks of LLMs
- Neural networks and deep learning in LLMs
- Training LLMs: data, algorithms, and computational resources
Implementing LLMs in Chatbots
- Integration strategies for LLMs in existing systems
- Designing conversational flows and user interactions
- Ensuring contextual understanding and coherence
Enhancing Chatbot Responsiveness
- Techniques for real-time response generation
- Handling concurrent conversations
- Personalization and predictive support
User Experience and Interface Design
- Crafting user-friendly chatbot interfaces
- Visual and textual cues for better engagement
- Feedback loops and continuous improvement
Ethical Considerations and Compliance
- Privacy and data security with LLMs
- Ethical use of AI in customer support
- Adhering to industry standards and regulations
Testing and Deployment
- Quality assurance and testing methodologies
- Deployment strategies for scalability and reliability
- Monitoring and maintenance of chatbot systems
Case Studies and Real-world Applications
- Analyzing successful implementations of LLM chatbots
- Lessons learned and best practices
- Future trends and innovations in AI-driven customer support
Project and Assessment
- Designing and building an LLM-based chatbot
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps
Requirements
- An understanding of basic programming concepts
- Experience with Python programming is recommended but not required
- Familiarity with basic machine learning concepts is beneficial
Audience
- Customer support professionals
- IT professionals
- Business analysts
14 Hours
