University of Edinburgh

The course examines key aspects of popular religious culture during the early modern period in Europe which witnessed the transformation of religious life associated with the Protestant and Catholic Reformations. It deals specifically with religious ideas and devotional practices at a popular level and the changes introduced by both Protestant and Catholic reformers. As part of the spectrum of belief it examines ideas concerning magic and witchcraft and it includes a study of the witch hunting which swept through Europe in the 16th and 17th centuries. Throughout the course particular attention will be given to the role of women in churches and society and how they were affected by the religious upheavals of the period. 

This course focuses on approaches relating to representation, reasoning, and planning for solving real world inference. The course illustrates the importance of using a smart representation of knowledge such that it is conducive to efficient reasoning, and the need for exploiting task constraints for intelligent search and planning. The notion of representing action, space, and time is formalized in the context of agents capable of sensing the environment and taking actions that affect the current state. There is also a strong emphasis on the ability to deal with uncertain data in real world scenarios, and the planning and reasoning methods needed for inference in probabilistic domains. 

On this course, students read a range of Buddhist literature from different historical and geographical contexts, and use this literature to explore key Buddhist ideas, themes, and literary forms.
 

This course covers some of the linguistic and algorithmic foundations of natural language processing (NLP). It builds on algorithmic and data science concepts developed in previous courses, applying these to NLP problems. It also equips students for more advanced NLP courses. The course is strongly empirical, using corpus data to illustrate both core linguistic concepts and algorithms, including language modeling, part of speech tagging, syntactic processing, the syntax-semantics interface, and aspects of semantic and pragmatic processing. The theoretical study of linguistic concepts and the application of algorithms to corpora in the empirical analysis of those concepts are interleaved throughout the course.