Overview

This course focuses on integrating and leveraging OpenAI APIs to build real-world AI applications, with a focus on ChatGPT, DALL-E, and Whisper. It will help learners develop practical skills to apply AI models to NLP tasks, AI-generated art, and automated processes. By covering the most important AI development tools, the course provides a strong foundation for working with cutting-edge technology. Throughout this course, you’ll dive into the core concepts and best practices of using OpenAI APIs. You’ll work on hands-on projects that integrate ChatGPT, Whisper, and DALL-E into real-world applications. Emphasizing practical experience, the course will take you through step-by-step tutorials that include code snippets, deployment techniques, and much more. What sets this course apart is its comprehensive, project-based approach. You won’t just learn the theory – you’ll also engage in creating real-world AI applications that can be deployed. We focus on desktop and web applications, ensuring you understand both the integration of APIs and the deployment process. This course is perfect for Python developers, software engineers, and anyone interested in AI development. A basic understanding of Python and APIs is required for the best learning experience.

Syllabus

Getting Started with the ChatGPT API for NLP Tasks

In this section, we cover the ChatGPT API setup and basic response examples for NLP tasks.

Building a ChatGPT Clone

In this section, we build a ChatGPT clone with Flask and OpenAI API, focusing on real-time chat and context retention.

Creating and Deploying a Code Bug-Fixing Application Using Flask

In this section, we build a Flask-based SaaS app integrating ChatGPT for code error fixes and deploy it to Azure for global access.

Integrating the Code Bug-Fixing Application with a Payment Service

In this section, we integrate Stripe API for payment processing and set up a SQL database to track user activity and transactions in a ChatGPT application.

Quiz Generation App with ChatGPT and Django

In this section, we build a quiz generation app using Django and ChatGPT, focusing on AI integration, database storage, and practical web development techniques.

Language Translation Desktop App with the ChatGPT API and Microsoft Word

In this section, we explore building a language translation desktop app using ChatGPT API and Microsoft Word. Key concepts include API integration, Tkinter UI development, and NLP techniques for real-time document translation.

Building an Outlook Email Reply Generator

In this section, we explore integrating Outlook API with GPT-4 to generate personalized email replies, using tkinter for a user-friendly interface and enhancing productivity through AI-driven automation.

Essay Generation Tool with PyQt and the ChatGPT API

In this section, we explore building a PyQt desktop app with ChatGPT API integration, enabling essay generation and API token control for customized AI responses.

Integrating the ChatGPT and DALL-E APIs: Building an End-to-End PowerPoint Presentation Generator

In this section, we explore integrating DALL-E and ChatGPT APIs to automate PowerPoint creation.

Speech Recognition and Text-to-Speech with the Whisper API

In this section, we explore using the Whisper API for speech-to-text conversion and multilingual translation, focusing on practical applications like voice transcription and long audio processing with PyDub.

Choosing the Right ChatGPT API Model

In this section, we explore selecting ChatGPT API models, optimizing chat completion parameters, and understanding AI model limitations for effective application development.

Fine-Tuning ChatGPT to Create Unique API Models

In this section, we explore fine-tuning ChatGPT using JSONL data to create domain-specific models. Key concepts include dataset preparation, transfer learning, and deploying models for task-specific responses.