This topic will provide a basic understanding of Intelligent Systems and their applications, including a basic understanding and broad overview of Artificial Intelligence and Heuristic Search methodologies, and supervised and unsupervised Machine Learning and Data Mining technologies. The topic provides a balance of theory and practice, with two lectures on theory or philosophy being complemented by seminar-style case studies on specific applications, including guest speakers. Practical work is largely undertaken and assessed in weekly computing laboratory sessions, with a variety of assignments including specification, programming and written tasks. Specific areas to be covered include methodologies and philosophical issues, the relationship of intelligent systems to human intelligence and cognitive science, applications to knowledge engineering, knowledge discovery, language processing, text and data mining, as well as selected topics relating to cognition, perception, visualization and classification/clustering.
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