In this module, we will dive into the diverse applications of ChatGPT and explore how to leverage its power for real-world tasks. From text completion to complex use cases like sentiment analysis and code generation, you’ll gain hands-on experience applying ChatGPT's abilities. By the end of this section, you'll be equipped to tackle a wide range of challenges using the OpenAI API.

In this module, we will explore the critical parameters that govern how the OpenAI API generates responses. You’ll learn how to fine-tune the temperature, tokens, and stop sequences for better output control, while diving into advanced features like top P and penalties for improved response variety and relevance. By the end, you'll have a deeper understanding of how to optimize your API interactions for different use cases.

In this module, we will dive into OpenAI’s streaming capabilities, enabling real-time interaction with the API. You will learn how to establish a stream connection, listen for events in your backend, and handle the dynamic flow of data in your frontend application. By the end, you'll be equipped to build highly interactive and responsive applications powered by OpenAI’s stream API.

In this module, we will explore the art of prompt engineering to maximize the effectiveness of your interactions with ChatGPT. You’ll learn practical techniques like specifying context, refining response formats, and using shot-based approaches to enhance the model's performance. By mastering these strategies, you'll be able to craft more precise, relevant, and engaging prompts for a wide range of use cases.

In this module, we will guide you through the process of building a fully functional PDF book summarizer app. You’ll learn how to create the app’s interface, extract text from uploaded PDFs, and break the text into manageable chunks for summarization. By the end, you'll have developed an app that processes large PDF files and generates clear, concise summaries using OpenAI’s API.

In this module, we will explore the Chat API and build a live weather app that interacts with real-time data. You’ll learn how to send your first request to the Chat API, compare different models (GPT-3 vs GPT-4), and use function calling to connect to external services. By the end, you’ll be able to create an app that retrieves weather data and presents it in natural language through ChatGPT.

In this module, we will guide you through the creation of an interactive chatbot app where users can converse with historical and contemporary figures like Einstein, Steve Jobs, and Bill Gates. You’ll learn how to design the user interface, manage message states, and dynamically adjust the conversation based on the selected personality. By the end, you’ll have a chatbot that responds in character, providing a personalized experience for each user.

In this module, we will explore the concept of embeddings and how they are used to measure the similarity between text inputs. You’ll learn how to create a simple app that generates embeddings for user inputs and calculates the cosine similarity between them. Additionally, you’ll gain insight into the costs associated with generating embeddings, providing a well-rounded understanding of this powerful NLP technique.

In this module, you will build an exciting book recommendations app that suggests books based on user preferences. You’ll start by downloading and converting a book dataset, then calculate embeddings for each book description. You’ll compare user inputs with these embeddings to find the most relevant book recommendations, and finally, display these recommendations in an interactive user interface. To add a visual touch, you’ll even map your book data in a 2D space using Atlas. By the end of the module, you’ll have a fully functional book recommendation app!

In this module, we will guide you through creating an app that allows users to interact with any PDF document via a chatbot interface. You’ll learn how to extract text from PDFs, split the content into chunks, and calculate embeddings to match user queries with relevant sections. Additionally, you’ll build the chat container and manage the flow of messages between the user and the PDF content. By the end of this section, you will have a functional app that enables conversational access to PDF documents.

In this module, you will explore the exciting world of image generation using DALL-E. You will learn how to integrate the DALL-E model into an app to create images from text prompts. The module will cover displaying the generated images in your React app, and also how to implement image storage with a POST request. By the end of this section, you’ll have a fully functioning text-to-image app powered by DALL-E.

In this module, you will create a powerful image editing app that combines the artistic capabilities of DALL-E with the flexibility of a canvas interface. You will start by building the user interface and setting up image uploads, then move on to drawing and masking features within the canvas. Finally, you will learn how to send requests to the server for applying edits and saving both original and masked images. By the end, you’ll have a fully functional image editing app capable of generating and modifying images based on user interactions.

In this module, you will learn how to create an app that takes an image input and generates different variations using DALL-E. You will explore how to interact with the OpenAI API to produce these variations and display them in your application. By the end of this section, you’ll have built an app that gives users the ability to see multiple artistic renditions of any uploaded image.

In this module, you will create an audio-to-text transcription app powered by OpenAI's Whisper model. You’ll learn how to build the user interface for audio file uploads, implement React handlers, and set up server-side functionality to save and transcribe audio files. By the end of this section, you’ll have a fully functional app that converts audio into text and leverages Whisper’s advanced features for accurate transcription.

In this module, you will develop an audio translation app that uses Whisper to convert spoken language from various audio files into English text. You’ll learn how to handle audio file uploads and integrate the Whisper API for seamless translation. By the end of this section, you’ll have a working app capable of translating audio content into text in real-time.

In this module, you will build a speech-to-text app by leveraging OpenAI's Whisper model for accurate transcription. You will adapt code from earlier projects to create a smooth and efficient transcription experience. By the end of this section, you’ll have an app that transcribes real-time speech into text, ready to be used in various applications.

In this module, you will create an app that translates spoken language into English text using Whisper. You’ll learn how to capture and process speech, then send it to Whisper for translation. By the end of this section, you’ll have a fully functional app capable of translating speech into English instantly.