Build AI-Powered Apps: ChatGPT, Vision, Voice & More

Have you ever wondered how developers are building AI features into their apps—like AI chatbots, image generators, voice narration, or document readers? Most of them aren’t training models from scratch. They’re simply using existing APIs smartly.

This course will show you how to do exactly that.

In “Build AI-Powered Apps Using APIs: ChatGPT, Vision, Voice & More,” I’ll walk you through the real-world process of integrating AI into your applications using powerful APIs—without needing to be a data scientist or ML engineer.

You’ll learn how to use OpenAI’s APIs for tasks like generating chat responses, creating images, converting text to speech, and even analyzing image data. We’ll also explore other providers like Google Cloud, Replicate, Hugging Face, ElevenLabs, and how to host AI models locally using Ollama.

Here’s a breakdown of what I’ll be teaching:

🔊 Text-to-Speech (TTS)

Bring voice to your apps. You’ll use APIs like OpenAI’s TTS or ElevenLabs to convert text into realistic speech. We’ll compare voices, speeds, languages, and how to embed playback in your UI.

🎙️ Speech-to-Text (STT)

I’ll also show you how to transcribe spoken audio using OpenAI’s Whisper and Google’s Speech-to-Text. You’ll learn how to handle audio files, manage languages and accents, and convert voice to usable content or commands.

🖼️ Image Vision (Data from Images)

Using GPT-4 Vision and Google Vision API, we’ll extract text, detect tables, read documents, and even analyze images for object detection. This is useful for document parsing, invoice reading, and more.

💻 Run AI Models Locally with Ollama

Not comfortable sending everything to cloud APIs? I’ll teach you how to run powerful models like LLaMA3, Mistral, or Gemma on your own system using Ollama. You’ll learn how to query these models locally through simple HTTP calls, and even switch between local and cloud fallback.

🔄 Combine Everything: Build Multimodal AI Apps

Finally, we’ll put everything together by creating small but complete applications that take voice input, understand images, generate chat-based replies, or create content from text and images—powered entirely by APIs.

🎓 What You’ll Get From This Course:

• Clear, working examples for every API

• Mini-projects after each major module

• Cheatsheets for API endpoints and prompt styles

• Deployment guidance using tools like Vercel or Docker

• A final capstone project that uses all learned skills

• Real code in JavaScript or Python (you can use either)

• Templates to plug into your own applications

By the end of the course, you’ll be able to build modern AI features into your own apps—without waiting for a library, without copying old tutorials, and without relying on expensive platforms.

You’ll understand how to think about APIs, what’s possible today with AI, and how to make it work in your projects—whether it’s a chatbot, AI designer, PDF analyzer, voice assistant, or smart input field.