The course objective is for students to learn about deep neural networks (deep learning), and how to leverage them in processing, understanding and mining for insights from text. The course starts with an introduction to neural networks and deep learning and then dives into essentials of representation learning like word and document embeddings. The course then moves onto more complex methodologies including convolutional neural networks and sequence models and deep transfer learning approaches including universal embeddings and transformers. Popular applications are also covered with hands-on tutorials and exercises including text classification, information extraction, recommenders, search, summarization, translation and more.