Getting started with ChatGPT

Give a booster shot to team productivity by adding ChatGPT capabilities to your apps.

Duration

5 Days

Level

Basic Level

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As per your team needs

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ChatGPT is a powerful language model developed by OpenAI that can generate human-like responses to natural language inputs. It is capable of understanding and generating text in a variety of languages and can be used for a wide range of applications, such as chatbots, customer service, and content creation. This outline is intended for Python developers who want to learn how to use ChatGPT in their projects.

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The target audience for this course is Python developers who have a basic understanding of programming concepts and want to learn how to incorporate natural language processing into their projects. This course is also suitable for individuals who have experience with other programming languages and want to learn Python for NLP.

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Introduction to ChatGPT

Overview of Generative AI (GPT, LLMs and DALE2)
Understand ChatGPT and its capabilities
Understanding the difference between language models and chatbots
Introduction to OpenAI API and how to access ChatGPT

Natural Language Processing Essentials

Language Model Fundamentals.
Review of fundamental NLP concepts such as tokenization, part-of-speech tagging, and named entity recognition
Understanding sentiment analysis and text classification
Text preprocessing techniques such as stemming and lemmatization

Building a Chatbot with ChatGPT

Understanding the design process of a chatbot
Choosing the right dataset for training ChatGPT
Preprocessing text data for use in ChatGPT
Fine-tuning a pre-trained ChatGPT model for specific use cases
Implementing ChatGPT into a chatbot using Python

Content Creation with ChatGPT

Overview of content creation with ChatGPT
Understanding the use of prompts and completions
Generating text using ChatGPT for various use cases such as article writing and summarization
Preprocessing text data for content creation
Implementing ChatGPT into a content creation application using Python

Advanced ChatGPT Techniques

Introduction to advanced concepts such as transfer learning and attention mechanisms
Fine-tuning ChatGPT for specific use cases
Understanding the limitations of ChatGPT and how to overcome them
Tips and tricks for optimizing ChatGPT performance and reducing model bias

Project Implementation

Applying the concepts learned in the course to a real-world project
Working with a team to design and build a ChatGPT application
Troubleshooting and optimizing the application for maximum performance

Best Practices and Ethics in ChatGPT

Understanding the ethical concerns and potential biases associated with using ChatGPT
Review of best practices for ensuring fair and unbiased results
Ethical considerations for the development and deployment of ChatGPT-powered applications
Strategies for responsible use of ChatGPT in sensitive or controversial applications

Future Developments in ChatGPT

Overview of the latest research and developments in the field of ChatGPT
Discussion of emerging use cases for ChatGPT
Opportunities for further development and improvement of ChatGPT technology

Conclusion and Next Steps

Recap of key concepts and skills learned in the course
Suggestions for further learning and development of ChatGPT skills
Guidance for continuing to improve and apply ChatGPT knowledge in future projects

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A basic understanding of Python programming
Familiarity with natural language processing concepts such as tokenization, part-of-speech tagging, and sentiment analysis
A working knowledge of machine learning concepts such as supervised and unsupervised learning
Some understanding of Language Models.

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Getting started with ChatGPT

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