Build an AI Video Watermark Remover with React & ONNX

About this course

Build a Real AI Product in the Browser — No Backend, No Python, No Server Costs

What if you could run a full AI model, not a wrapper around someone else's API, but a real machine learning model directly in the browser, with zero backend infrastructure? In this course, you'll build a complete AI-powered video watermark remover using React, Tailwind CSS, and ONNX Runtime Web, and you'll walk away understanding exactly how modern client-side AI applications work under the hood.

This isn't a toy demo. You'll build a production-style React application from the ground up with components, state management, styling, video processing, and AI inference, all running entirely on the user's device.

Why This Course Is Different

Most AI + web courses teach you to call an API and display the response. This course teaches you to run the model yourself, in the browser, using ONNX (Open Neural Network Exchange), the open format that lets machine learning models trained in PyTorch or TensorFlow run anywhere, including a browser tab.

You'll learn how ONNX Runtime Web intelligently selects between WebGPU (for GPU-accelerated inference) and WebAssembly (WASM) as a reliable fallback, how to cache large model files with IndexedDB so users never redownload them, and how to wire all of this into a clean, modern React front end.

What You'll BuildA fully functional web app where users upload a video, the app loads an ONNX model directly in the browser, processes each frame client-side, and returns a clean, watermark-free result with no file ever touching a server.

Technologies & Concepts CoveredReact: component architecture, props, and modern app structure

React Hooks: use

State, use

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