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This course covers generative AI with OpenAI’s ChatGPT, emphasizing prompt design and practical uses in marketing, research, and code generation.

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OpenAI aims to leverage artificial intelligence (AI) for the benefit of humanity. With the launch of ChatGPT, it has introduced a large-scale application of generative AI to create new content using machine learning algorithms. OpenAI offers a set of pretrained, ready-to-use models that can be consumed by the general public. 

This course starts with a basic introduction to generative AI, OpenAI, and ChatGPT, along with their potential use cases. It pitches the significance of prompt engineering with some practical and ethical considerations. You’ll explore various application domains where ChatGPT can enhance productivity, including marketing, research, and code generation. 

After completing this course, you’ll have the knowledge to explore the generative AI field and start using ChatGPT and OpenAI’s model APIs in your own projects while keeping some technical considerations in mind, including prompt design and bias mitigation.

Modern Generative AI with ChatGPT and OpenAI Models

By providing contract templates for common agreements

By flagging potential issues in contracts

By offering clear explanations of technical terms in contracts

How can AOAI’s models assist in contract analysis?

How can AOAI’s models assist in contract analysis?

To identify frequently asked questions for agents

To analyze sentiment in customer interactions

To automatically create tickets in the CRM with relevant information

To provide a relevant knowledge base for customer-facing chatbots

What is the primary goal of implementing features like parameter extraction from call transcripts in a call center scenario?

What is the primary goal of implementing features like parameter extraction from call transcripts in a call center scenario?

To provide information and answer customer questions

To automatically create tickets in the CRM

To handle each request more efficiently by directing it to the relevant department

In the context of customer requests, what is the purpose of classifying transcripts into categories such as reporting issue, claim handling, and general inquiry?

In the context of customer requests, what is the purpose of classifying transcripts into categories such as reporting issue, claim handling, and general inquiry?

Embedding helps generate numerical vectors for medical terms.
 

Embedding assists in understanding the semantic relationships between words.

Embedding is used to identify related topics not apparent from the search query.

Embedding ensures accurate search results by focusing on keyword-based algorithms.

What role does embedding play in semantic search, particularly in the context of medical documentation and papers?

What role does embedding play in semantic search, particularly in the context of medical documentation and papers?

Test your understanding of the concepts covered in this chapter.

Getting Started

Introduction to Generative AI

OpenAI and ChatGPT—Beyond the Market Hype

Getting Familiar with ChatGPT

Understanding Prompt Design

Boosting Day-to-Day Productivity with ChatGPT

Developing the Future with ChatGPT

Mastering Marketing with ChatGPT

Research Reinvented with ChatGPT

OpenAI and ChatGPT for Enterprises—Introducing Azure OpenAI

Trending Use Cases for Enterprises

Epilogue and Final Thoughts

Appendix

Quiz: Trending Use Cases for Enterprises