This module introduces students to the basic linguistic ideas needed for computational processing of text (morphology, syntax, semantics, discourse cohesion) and to how their properties can be understood computationally. With this in hand, it then introduces computational methods for text processing, for example, symbolic parsing models, basic text processing, probabilistic models, vector semantics, and deep learning architectures as well as applications in text classification, sentiment analysis, word prediction and text generation. It considers some of the ethical, environmental and research issues raised and includes discussion of the range of career routes that students' learning is relevant to.

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