A real-time sign language recognition system using Python is demonstrated, utilizing OpenCV for hand tracking and Google's MediaPipe for joint identification. The process involves collecting data, training a feed-forward neural network, and testing the model. Challenges include the need for diverse training data to improve accuracy across different hand signs.