Introduction to ChatGPT

Learn via : Virtual Classroom / Online
Duration : 3 Days
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ChatGPT is a language model developed by OpenAI. The name “ChatGPT” means that this model can be used to chat with people. ChatGPT is an advanced artificial intelligence model with natural language understanding and generation capabilities.

ChatGPT is trained using large amounts of text data and can then interact with people in real time. The model can generate meaningful and consistent responses based on text inputs. ChatGPT can answer questions, offer suggestions, make explanations, tell stories, and maintain general conversations on a variety of topics.

OpenAI developed ChatGPT primarily by building on top of GPT-3 and is constantly making improvements and updates. ChatGPT serves as an artificial intelligence tool that can be used in many application areas, from email writing assistants to customer service chatbots.

ChatGPT tries to understand the patterns between texts by learning the structure and relationships of the language. Thus, it can produce an output that matches the given text input. Because the model is pre-trained, it can provide answers based on current and valid information.


Module 1: Introduction to Conversational AI

  • Overview of Conversational AI and its applications
  • Introduction to ChatGPT and its capabilities
  • Ethical considerations and challenges in Conversational AI

Module 2: Understanding Language Models

  • Basics of language modeling
  • Introduction to GPT (Generative Pre-trained Transformer) architecture
  • Key concepts: self-attention, transformer blocks, decoding, etc.

Module 3: Data Collection and Preprocessing

  • Techniques for collecting conversational data
  • Data preprocessing and formatting for training ChatGPT
  • Handling noise, biases, and ethical concerns in training data

Module 4: Training ChatGPT

  • Overview of training process and resources required
  • Fine-tuning strategies and transfer learning
  • Hyperparameter tuning and model selection

Module 5: Evaluating and Improving ChatGPT

  • Metrics for evaluating conversational agents
  • Techniques for improving model performance
  • Handling biases and improving fairness in ChatGPT

Module 6: Deploying ChatGPT

  • Considerations for deploying ChatGPT in real-world applications
  • Integration with chat platforms and APIs
  • Monitoring and managing user interactions with ChatGPT

Module 7: ChatGPT Best Practices and Guidelines

  • Designing conversational flows and prompts
  • Handling sensitive and offensive content
  • Ensuring user safety and privacy

Module 8: Advanced Topics in Conversational AI

  • Dialogue management and context handling
  • Multi-turn conversations and user intent recognition
  • Reinforcement learning for conversational agents

Module 9: Future Directions and Ethical Considerations

  • Current research trends in Conversational AI
  • Ethical considerations in developing and deploying ChatGPT
  • Responsible AI practices and mitigating biases


There are no prerequisites for this course.