ChatGPT for Programmers complete course in 2025

Published On: June 13, 2025

ChatGPT for Programmers This course empowers programmers to harness the power of ChatGPT and OpenAI’s APIs to create intelligent, AI-driven applications in a matter of hours.

Through hands-on coding projects, step-by-step tutorials, and real-world examples, learners will master the integration of ChatGPT into web, mobile, and desktop applications.

Designed for developers with basic programming knowledge, this course focuses on practical skills to build chatbots, content generators, and other AI-powered tools using Python and JavaScript.

Duration: 12 hours
Level: Beginner to Intermediate
Prerequisites: Basic knowledge of Python or JavaScript, familiarity with APIs, and a willingness to explore AI.
Instructor: Inspired by Mike Wheeler and the Mike Wheeler Media Team
Rating: 4.6 (2,345 ratings)

Table of Contents

Course Objectives

Understand how ChatGPT and large language models (LLMs) work at a high level.
Learn to integrate OpenAI’s APIs into applications using Python and JavaScript.
Build AI-powered applications such as chatbots, content generators, and automation tools.
Explore advanced prompting techniques to optimize ChatGPT outputs.
Deploy AI applications to cloud platforms for real-world use.
Gain hands-on experience through practical, portfolio-ready projects.

Course Curriculum

Module 1: Introduction to ChatGPT and AI for Programmers

Duration: 1.5 hours
Objective: Grasp the basics of ChatGPT and its role in programming.
Lessons:

What is ChatGPT?

Overview of ChatGPT and its underlying GPT architecture.

Differences between traditional programming and AI-driven development.

Use cases for programmers: automation, chatbots, and content creation.

Understanding Large Language Models (LLMs)

High-level explanation of Transformers and LLMs.

How ChatGPT processes and generates text.

Setting Up the Environment

Installing Python, Node.js, and required libraries (e.g., requests, openai).

Obtaining an OpenAI API key.

Introduction to REST APIs and Postman for testing API calls.

Hands-On: First API Call

Making a simple API call to ChatGPT using Python.

Exploring API response structure.

Project: Create a basic text generator using the OpenAI API.

Module 2: Mastering OpenAI APIs

Duration: 2.5 hours
Objective: Learn to use OpenAI APIs for various AI tasks.
Lessons:

Introduction to OpenAI APIs

Overview of OpenAI’s API endpoints (completions, chat, embeddings).

Understanding models (e.g., GPT-3.5, GPT-4).

Working with the Chat Completions API

Structuring API requests for conversational AI.

Managing parameters: temperature, max_tokens, and system prompts.

Error Handling and Rate Limits

Best practices for handling API errors and retries.

Managing API rate limits and costs.

Hands-On: Building a Q&A System

Creating a question-answering tool using the Chat Completions API.

Testing with real-world queries.

Project: Develop a Python script that uses the OpenAI API to answer user questions dynamically.

Module 3: Advanced Prompt Engineering

Duration: 2 hours
Objective: Optimize ChatGPT outputs using advanced prompting techniques.
Lessons:

What is Prompt Engineering?

Importance of crafting effective prompts for desired outputs.

Types of prompts: zero-shot, one-shot, few-shot, and chain-of-thought.

Designing Robust Prompts

Structuring prompts for code generation, debugging, and content creation.

Using delimiters and context for clarity.

Iterative Prompt Testing

Techniques for refining prompts based on outputs.

Debugging unexpected AI responses.

Hands-On: Prompt Optimization

Writing prompts for specific tasks (e.g., generating HTML, writing unit tests).

Comparing outputs for different prompt variations.

Project: Build a code snippet generator that produces Python functions based on user-defined prompts.

Module 4: Building AI-Powered Applications with Python

Duration: 3 hours
Objective: Develop AI-driven applications using Python and OpenAI APIs.
Lessons:

Creating a Chatbot with Python

Building a conversational chatbot interface using Streamlit.

Integrating ChatGPT for real-time responses.

Automating Tasks with ChatGPT

Using ChatGPT to generate emails, reports, or documentation.

Automating repetitive coding tasks (e.g., boilerplate code).

Integrating with External Data

Combining ChatGPT with CSV or JSON data for personalized outputs.

Using libraries like Pandas for data processing.

Hands-On: Chatbot Development

Building a customer support chatbot with Streamlit and OpenAI API.

Project: Create a Python-based chatbot for a simulated customer service scenario.

Module 5: Building AI Web Apps with JavaScript

Duration: 3 hours
Objective: Integrate ChatGPT into web applications using JavaScript.
Lessons:

Introduction to JavaScript and OpenAI

Setting up a Node.js environment for OpenAI APIs.

Using the axios library for API calls.

Building a Web-Based Chat Interface

Creating a front-end with HTML, CSS, and JavaScript.

Connecting to the OpenAI API for chat functionality.

Enhancing User Experience

Adding features like chat history and real-time typing indicators.

Styling the interface with CSS frameworks (e.g., Tailwind CSS).

Hands-On: Web Chatbot

Building a browser-based chatbot using JavaScript and OpenAI.

Project: Develop a web-based AI chatbot that runs in the browser and supports real-time conversations.

Module 6: Deployment and Best Practices

Duration: 1.5 hours
Objective: Deploy AI applications and learn best practices for production.
Lessons:

Deploying AI Apps to the Cloud

Deploying Python apps to Heroku or Render.

Deploying JavaScript apps to Vercel or Netlify.

Securing API Keys

Storing API keys securely using environment variables.

Best practices to avoid key exposure.

Monitoring and Cost Management

Tracking OpenAI API usage to manage costs.

Implementing logging for debugging.

Hands-On: Deployment

Deploying a Python or JavaScript chatbot to a cloud platform.

Project: Deploy a chatbot to a cloud platform and test its functionality in a live environment.

Module 7: Capstone Project

Duration: 2 hours
Objective: Synthesize all skills in a comprehensive project.
Capstone Project: Build a full-stack AI-powered application that integrates ChatGPT into a real-world use case. Examples include:

A code assistant that generates, debugs, and explains code snippets.
A content creation tool for generating blog posts or social media content.
An automated support system that answers FAQs using a knowledge base.
The project includes:
A front-end interface (using Streamlit, Gradio, or Streamlit JavaScript).
A back-end with Flask, FastAPI, or Node.js.
Integration with OpenAI APIs for dynamic responses.
Cloud deployment with monitoring.

Course Features

Hands-On Coding: 10+ hours of coding exercises and project work.
Real-World Projects: Build portfolio-ready AI applications like chatbots and automation tools.
Community Support: Access to a dedicated Discord or forum for peer and instructor support.
Certificate of Completion: Earn a certificate to showcase your skills.
Lifetime Access: Revisit course materials anytime.

Target Audience

Programmers looking to integrate AI into their projects.
Developers interested in building chatbots and automation tools.
Professionals aiming to enhance productivity with AI-driven solutions.
Students exploring the intersection of AI and software development.

Learning Outcomes

By the end of this course, you will:

Confidently use OpenAI APIs to integrate ChatGPT into applications.
Build AI-powered chatbots and automation tools using Python and JavaScript.
Optimize AI outputs through effective prompt engineering.
Deploy AI applications to cloud platforms.
Create portfolio-ready projects showcasing AI skills.

Resources

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Additional Resources:

Code Repository: Access all project code on GitHub.
Supplementary Materials: Downloadable code snippets, API documentation, and sample datasets.
Recommended Tools: Python, Node.js, GitHub, OpenAI API, Streamlit, Flask, Gradio, FastAPI, Vercel, Heroku.

Enrollment Details

Platform: Udemy
Link: ChatGPT for Programmers
Discount: Check for current promotions (e.g., discounts for new users or limited-time offers).
Access: Lifetime access to course materials and updates.

About the Instructor

Mike Wheeler is a seasoned tech educator and founder of the Mike Wheeler Media, with over 20 years of experience teaching programming and emerging technologies.

Known for his practical, hands-on teaching style, Mike has helped thousands of developers adopt AI tools like ChatGPT to enhance their skill sets.

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