Detailed Course Information |
Spring 2024 Semester
May 15, 2024 |
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| DS 5230 - Unsupervised Machine Learning and Data Mining |
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Introduces unsupervised machine learning and data mining, which is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest. Offers a broad view of models and algorithms for unsupervised data exploration. Discusses the methodological foundations behind the models and the algorithms, as well as issues of practical implementation and use, and techniques for assessing the performance. Includes a term project involving programming and/or work with real-life data sets. Requires proficiency in a programming language such as Python, R, or MATLAB.
4.000 Credit hours 4.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Lecture Data Science Department Course Attributes: Graduate CCIS Data Sci Cert, NUpath Capstone Experience, NUpath Writing Intensive Restrictions: Must be enrolled in one of the following Programs: MS Data Science MSCS Computer Science - Align MS Economics MSCS Computer Science MS Artificial Intelligence MS Data Science - Align Must be enrolled in one of the following Levels: Undergraduate Graduate Must be enrolled in one of the following Classifications: Graduate Prerequisites: |
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