This is a code-first introduction to natural language processing originally taught at the University of San Francisco. The course covers traditional NLP techniques like TF-IDF, SVD, and Naive Bayes alongside deep learning approaches including RNNs for translation and Transformer architectures. Lessons are delivered via Jupyter Notebooks using Python libraries such as sklearn, nltk, PyTorch, and fastai.