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The NVIDIA Jetson Nano Developer Kit is one of the most powerful and affordable edge AI platforms available today. It enables developers, students, and hobbyists to build and deploy real time AI applications such as object detection, voice processing, robotics navigation, smart surveillance, and IoT automation  all on a compact GPU accelerated device.

This guide walks you through the entire setup process end to end, starting from preparing the microSD card, flashing JetPack OS, configuring networking, enabling SSH, scanning the device on your LAN, and completing the desktop onboarding steps.
Every stage is illustrated with images, so even first time users can follow along easily.

By the end of this setup, your Jetson Nano will be fully ready to deploy deep learning models, run TensorRT optimized inference, manage Docker containers, and integrate with larger AI/IoT pipelines.

1. Preparing Your Jetson Development Kit

Before getting started, ensure you have a Jetson device, a computer with internet access, a microSD card (32GB recommended), and an SD card reader. You will download JetPack OS and use Balena Etcher to flash the system image onto the SD card.

Setting up the Jetson Nano correctly from the beginning is crucial because the device relies heavily on optimized system components that come bundled with JetPack OS. This OS includes CUDA, cuDNN, TensorRT, and essential GPU drivers all of which are required for running modern AI workloads. A clean and properly flashed SD card ensures that the Jetson boots smoothly, recognizes all onboard hardware, and operates with full GPU acceleration.

During the SD preparation stage, tools like SD Card Formatter and Balena Etcher ensure the card is formatted correctly and the JetPack image is written without corruption. Windows cannot interpret Linux EXT4 partitions, so seeing “unallocated space” in Disk Management is completely normal and confirms that the flash was successful.

Download the SD card Formatter and install them.