Course Outline

Introduction to AI-Driven NLG

  • Overview of Natural Language Generation (NLG)
  • Role of NLG in conversational AI systems
  • Key differences between NLU and NLG

Deep Learning Techniques for NLG

  • Transformers and pre-trained language models
  • Training models for dialogue generation
  • Handling long-term dependencies in conversation

Chatbot Frameworks and NLG

  • Integrating NLG with chatbot platforms (e.g., Rasa, BotPress)
  • Generating personalized responses for chatbots
  • Improving user engagement through contextual AI

Advanced NLG Models for Virtual Assistants

  • Using GPT-3, BERT, and other cutting-edge models
  • Generating multi-turn dialogues with AI
  • Improving fluency and naturalness in virtual assistant responses

Ethical and Practical Considerations

  • Bias in AI-generated content and how to mitigate it
  • Ensuring transparency and trustworthiness in chatbot interactions
  • Privacy and security considerations for virtual assistants

Evaluation and Optimization of NLG Systems

  • Evaluating NLG quality: BLEU, ROUGE, and human evaluation
  • Tuning and optimizing NLG performance for real-time applications
  • Adapting NLG for domain-specific use cases

Future Trends in NLG and Conversational AI

  • Emerging techniques in self-supervised learning for NLG
  • Leveraging multimodal AI for more interactive conversations
  • Advances in context-aware conversational AI

Summary and Next Steps

Requirements

  • Strong understanding of Natural Language Processing (NLP) concepts
  • Experience with machine learning and AI models
  • Familiarity with Python programming

Audience

  • AI developers
  • Chatbot designers
  • Virtual assistant engineers
 21 Hours

Delivery Options

Private Group Training

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  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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