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Spring 2024 Semester
Oct 31, 2024
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Information Select the desired Level or Schedule Type to find available classes for the course.

DS 5220 - Supervised Machine Learning and Learning Theory
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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