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Course Outline
Introduction to Conversational AI and Small Language Models (SLMs)
- Fundamentals of conversational AI
- Overview of SLMs and their advantages
- Case studies of SLMs in interactive applications
Designing Conversational Flows
- Principles of human-AI interaction design
- Crafting engaging and natural dialogues
- User experience (UX) considerations
Building Customer Service Bots
- Use cases for customer service bots
- Integrating SLMs into customer service platforms
- Handling common customer inquiries with AI
Training SLMs for Interaction
- Data collection for conversational AI
- Training techniques for SLMs in dialogue systems
- Fine-tuning models for specific interaction scenarios
Evaluating Interaction Quality
- Metrics for assessing conversational AI
- User testing and feedback collection
- Iterative improvement based on evaluation
Voice-Enabled and Multimodal Interactions
- Incorporating voice recognition with SLMs
- Designing multimodal interactions (text, voice, visuals)
- Case studies of voice assistants and chatbots
Personalization and Contextual Understanding
- Techniques for personalizing interactions
- Context-aware conversation handling
- Privacy and data security in personalized AI
Ethical Considerations and Bias Mitigation
- Ethical frameworks for conversational AI
- Identifying and mitigating biases in interactions
- Ensuring inclusivity and fairness in AI communication
Deployment and Scaling
- Strategies for deploying conversational AI systems
- Scaling SLMs for widespread use
- Monitoring and maintaining AI interactions post-deployment
Capstone Project
- Identifying a need for conversational AI in a chosen domain
- Developing a prototype using SLMs
- Testing and presenting the interactive application
Final Assessment
- Submission of a capstone project report
- Demonstration of a functional conversational AI system
- Evaluation based on innovation, user engagement, and technical execution
Summary and Next Steps
Requirements
- Basic understanding of Artificial Intelligence and Machine Learning
- Proficiency in Python programming
- Experience with Natural Language Processing concepts
Audience
- Data scientists
- Machine learning engineers
- AI researchers and developers
- Product managers and UX designers
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
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