DeepSpeech is a neural network architecture first published by Baidu's research team. Mozilla created an open-source implementation of this paper, known as "Mozilla DeepSpeech". The original DeepSpeech paper from Baidu popularized the concept of "end-to-end" speech recognition models. These models directly output characters or words from audio input, unlike traditional models that predict phonemes and then convert them to words in a separate process. The goal of end-to-end models like DeepSpeech is to simplify the speech recognition pipeline into a single model. Additionally, the theory introduced by Baidu's research paper suggests that training large deep learning models on large amounts of data can yield better performance than classical speech recognition models. Mozilla DeepSpeech offers pre-trained speech recognition models and tools for users to train their own DeepSpeech models. Users can also contribute to DeepSpeech's public training dataset through the Common Voice project. In this tutorial, we covered how to install and transcribe audio files with the Mozilla DeepSpeech library. We discussed the basic DeepSpeech example and real-time speech recognition example using Python.