MIT Sloan's Rama Ramakrishnan continues his 15.773 Hands-On Deep Learning course with an introduction to natural language processing. He covers how text gets converted into numerical form through vectorization, walks through the bag-of-words model as a foundational representation technique, and discusses its strengths and limitations for capturing meaning in text. The session includes a live demonstration in Google Colab, showing how these concepts translate into working code for processing and analyzing language data. Aimed at students already familiar with basic deep learning concepts, this lecture sets up the vocabulary and techniques needed before moving into more advanced NLP architectures like embeddings and neural network based language models later in the course.