### Description

This is an end-to-end course on OpenAI covering all the aspects ranging from beginner to advanced scenarios.&nbsp;

It is based on a use-case-driven approach for developers to focus on modules that are aligned with their needs or a specific area. The demos and labs act as templates for the students to customize the code for their requirements easily.

**At a high level, this course covers the following topics:**&nbsp;

*   Big Picture of OpenAI:&nbsp;Understand the structure of OpenAI models, tokens, prompt engineering, available models, tools, libraries, services, free tier, and the pricing structure.&nbsp;
*   Models of OpenAI: Understand the large language models and image generators offered by OpenAI, along with the critical use cases and scenarios.
*   Prompt Engineering: Explain what prompt engineering is and define the best practices of providing prompts for the generative AI models. We will use ChatGPT and OpenAI Playground to explore prompt engineering
*   Text Completion: This section explores auto-completion of text based on the prompts. It introduces the key concepts of tokens and how to optimize the prompts for cost and accuracy.&nbsp;
*   Code Completion: Extending the concept of code completion, we will learn how OpenAI can generate code based on comments and prompts.&nbsp;
*   Q&A Generation: This section explores how OpenAI models can generate Q&A based on an input text.&nbsp;
*   Image Generation: Based on DALL-E 2, we will explore how to apply prompt engineering to generate images.
*   Building a Chatbot: Using the OpenAI Chat API, we will build a custom chatbot that can respond to various queries.&nbsp;
*   Content Moderation: In this section, we will explore how to identify hate speech by invoking the right API exposed by OpenAI
*   Speech to Text Conversion: Based on the Whisper model, we will generate text from an audio file.
*   Fine-tuning Models: In this section, we will provide a custom dataset to GPT3 to generate a new fine-tuned model capable of answering questions based on the custom dataset.&nbsp;
*   Roadmap: This section includes possible features expected from OpenAI, such as the plugins.

Introduction

What is Generative AI

Getting Started with OpenAI

Exploring ChatGPT

Understanding Prompt Engineering

Understanding Tokens and API Parameters

Implementing Word Completion

Implementing Code Completion

Building an Interactive Chatbot

Performing Text Processing and Analysis

Using Word Embeddings For Dynamic Context

Fine-tuning GPT-3 with a Custom Dataset

Generating Images

Audio Transcription & Translation

Moderating Prompts with Moderating API

Summary and Next Steps

Mastering Generative AI with OpenAI

He has experience working with companies like Microsoft, Amazon Web Services, and Bell Labs, and he has held various technical and management roles in these organizations. Janakiram is also a public speaker and a prolific writer, contributing to several technology publications. He is known for his expertise in cloud computing, particularly around platforms like AWS, Azure, and Google Cloud Platform, as well as his insights on emerging technologies such as Kubernetes, microservices, serverless computing, IoT, and edge computing.

Janakiram MSV

Mastering Generative AI with OpenAI

Janakiram MSV

Description

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About the instructor

Janakiram MSV