Gain insights into prompt engineering for ChatGPT. Explore effective prompting techniques, applications in various domains, and limitations, enabling you to harness its power for professional, marketing, and academic tasks.

ChatGPT is one of the most advanced AI systems available today. In this course, you will dive into the world of generative AI and get the ability to effectively use it.

The course briefly explains the recent advances in generative AI, more specifically, ChatGPT. It covers the basics of prompting and then explains the best practices for effective prompting. Furthermore, it describes how ChatGPT can be harnessed for transforming, expanding, summarizing, or inferring information. Domain-specific use cases of ChatGPT are also discussed, such as using it for professional writing and for search engine optimization. Effective ChatGPT prompting techniques are also shared for the marketing and academic domains. It also briefly covers autoprompts, chatbots, and the limitations of ChatGPT. 

After taking this course, you will be able to master prompting and will have the knowledge to effectively use it.

Master ChatGPT Prompt Engineering

# What is ChatGPT? 
Language is essential for communication. Recent advances in the field of natural language processing (NLP) with advanced deep-learning concepts make it possible for machines to understand and generate human-like responses. Among the growing numbers of popular LLMs, one of the most employed language models is ChatGPT, developed by OpenAI. 

It is specifically designed to generate human-like responses to text-based conversations/prompts. In this lesson, we'll explore the working of ChatGPT, including its model architecture, training data, attributes, and more. We'll also discuss why ChatGPT is one of the most popular language models and how it is positioned in the broader domain of natural language processing.


ChatGPT is an advanced language model that can understand the meaning of the text. The giant version, GPT-3.5, has a lot of components that work together, which makes it very powerful. These components help ChatGPT understand the context of the text and generate appropriate responses.

ChatGPT is based on the GPT-3 architecture and uses a variant of the #key# autoregressive language modeling technique: A technique where a computer program predicts the next word in a sentence using probability based on the previous words. #key#. The model is trained and fine-tuned to generate text-based responses to input text using a probability distribution over the upcoming words. This approach helps ChatGPT to generate responses that are contextually appropriate and similar to human-like responses.

Learn about ChatGPT's features, attributes, and training data.

Introduction

Introduction to ChatGPT

Effective Prompting

Domain-Specific Prompting Tips With Examples

AutoPrompt, Chatbots, and Generative AI's Limitations

Conclusion

ChatGPT: Under the Hood

What is ChatGPT?

ChatGPT model