Detailed Course Information |
Spring 2024 Semester
May 15, 2024 |
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| DS 5220 - Supervised Machine Learning and Learning Theory |
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Introduces supervised machine learning, which is the study and design of algorithms that enable computers/machines to learn from experience or data, given examples of data with a known outcome of interest. Offers a broad view of models and algorithms for supervised decision making. 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-world 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 Robotics MS Economics MS Data Science 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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