This tutorial guides you through building, training, and testing a UNETR (U-Net with Transformers) model for hair segmentation using TensorFlow and Python. Learn the complete pipeline from loading the Figaro Hair Segmentation dataset to visualizing results. Master how UNETR combines Vision Transformers (ViT) with a U-Net-like decoder, implement patch creation for transformer models, develop custom Dice Loss functions, and run inference with OpenCV visualization. The 30-minute video covers installation, model building, training, and testing with practical code examples. Complete source code is available through the provided link, and additional resources for computer vision and visual language models are referenced in the description.