Course Criteria

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  • 1.00 - 6.00 Credits

    A year-long research and writing project in dance completed during the senior year under the close supervision of a tutor from the department. The student and tutor work to develop the project design. A project proposal must be submitted in writing and approved by the director of dance prior to registration for the course. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions..
  • 3.00 Credits

    Semester one of a two semester intensive research and writing course for accomplished and motivated upper-level students under the close supervision of a faculty member in the department or program. Students must take the initiative in seeking a faculty member to help in the design and supervision of the project. This is an individual enrollment course, and registration is carried out through consultation with the faculty mentor. Prerequisites: Permission of the instructor and Department/Program approval prior to registration. Individual departments or programs may prescribe particular requirements for eligibility for the bachelor's essay, particular procedures for the approval of proposals, and/or particular guidelines for the projects themselves. Declared dance major; instructor and department chair permission.
  • 3.00 Credits

    Semester two of a two semester intensive research and writing course for accomplished and motivated upper-level students under the close supervision of a faculty member in the department or program. Students must take the initiative inseeking a faculty member to help in the design and supervision of the project. This is an individual enrollment course, and registration is carried out through consultation with the faculty member. Prerequisite: DANC 499A
  • 3.00 Credits

    An introductory course on the use of computer-based tools and programs such as Python and SQL to analyze data sets for knowledge discovery. Students will explore and learn some of the basic principles and tools in data science. Topics include cleaning, visualizing, and interpreting data, databases, and cloud computing.
  • 3.00 Credits

    A course to introduce the structure of databases and the management of datasets for information extraction. Concepts include the relational and entity relationship models, and local and distributed storage and access. The preparation and management of datasets for analysis is covered, and includes data cleaning, reorganization and security. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions..
  • 3.00 Credits

    An intermediate course on using computer-based tools and programs to analyze and store data sets for knowledge discovery. Students will improve their knowledge and skills in three aspects of data science; data analysis, data management, and data modeling.
  • 0.00 Credits

    A student works under faculty supervision to learn a research method, to explore possible research topics, or to continue an ongoing study. The faculty member helps the student to determine the course goals and objectives, and supervises the execution of the project. The student will provide a written report to the faculty at the end of the semester. Students will receive a grade of "S" (Satisfactory) or "U" (Unsatisfactory) for the course. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions..
  • 3.00 Credits

    A capstone course to provide a synthesizing experience for DATA majors across all emphasis areas. This course provides hands-on experience in the practice of group-based software development. Student teams utilize development tools and techniques to implement software solutions to moderately complex problems. This project-based course provides a framework in which students apply their data mining and knowledge discovery skills, and gain understanding and insight into their synthesis with software engineering principles. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
  • 3.00 Credits

    This course covers key concepts in programming, pipeline development, data structures, algorithms, and complexity that are foundational to the fields of data science and analytics.
  • 3.00 Credits

    This course covers key concepts from linear algebra, optimization, probability and statistics, calculus, and discrete mathematics that are foundational to the fields of data science and analytics.
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