Course Search Results

• DPA 8600: Production Studio

  1.00 Credits

  Clemson University

  
  Students develop as accomplished visual problem solvers in a digital production team setting. As part of the studio experience, students take a production project from concept, through story development, character design, modeling and rigging, animation, lighting, and post production. May be repeated for a maximum of 12 credits. Preq: Enrollment in the Digital Production Arts program.
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• DPA 8800: Research Studio

  1.00 Credits

  Clemson University

  
  Students complete a project or projects, under the direction of a faculty adviser, in an area supporting personal goals and vision. Work may be individually or team oriented, and may be of a technical or an artistic nature. May be repeated for a maximum of six credits. Preq: Enrollment in the Digital Production Arts program.
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• DPA 8810: Selected Topics

  1.00 Credits

  Clemson University

  
  Advanced topics from current areas of interest in digital production. Topics vary from semester to semester. May be repeated for a maximum of 12 credits, but only if different topics are covered.
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• DPA 8910: MFA Thesis Research

  1.00 Credits

  Clemson University

  
  Students complete a studio research project, under the guidance of the student's advisor and thesis committee. The thesis project is developed to a refined degree, articulated in the form of a written document, and presented orally in a thesis defense. May be repeated for a maximum of six credits.
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• DSA 8010: Statistical Methods I

  3.00 Credits

  Clemson University

  
  Application of statistics in research, estimation, test of significance, analysis of variance, multiple comparison techniques, basic designs, mean square expectations, simple and multiple regression. Examples in data science topics of interest. Preq: Enrollment in the Data Science and Analytics Master of Science program.
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• DSA 8020: Statistical Methods II

  3.00 Credits

  Clemson University

  
  Extended coverage of methods introduced in DSA 8010, including multiple regression, experiment design, nonparametric methods, mixed models, categorical data analysis, multivariate methods and sampling designs, and use of statistical software. Case studies in data science and analytics are explored. Preq: Enrollment in the Data Science and Analytics Master of Science program and DSA 8010.
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• DSA 8030: Intro to Statistical Computing

  3.00 Credits

  Clemson University

  
  Introduction to statistical computing packages. Topics include data importation, reports, basic descriptive statistic computation, basic graphic preparation, and statistical analysis methods and procedures. Applications specific to data science and analytics are used. Preq: Enrollment in the Data Science and Analytics Master of Science program.
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• DSA 8070: Multivariate Analysis

  3.00 Credits

  Clemson University

  
  Covers applications in data science and analytics multivariate analysis, such as computer plots of multivariate observations, multidimensional scaling, multivariate tests of means, contrivances and equality of distribution, univariate and multivariate regressions and their comparisons MANOVA, principal components analysis, and factor analysis. Preq: Enrollment in the Data Science and Analytics Master of Science program and DSA 8020.
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• DSA 8280: Analytics Bootcamp

  3.00 Credits

  Clemson University

  
  This course offers an introduction into the DSA program and prepares students for its successful completion. Topics include CRISP-DM (an industry standard for data mining) and R/Python programming and data visualization. Examples given are specific to the data science and analytics field. To be taken Pass/No Pass only. May also be offered as MGT 8280. Preq: Enrollment in Data Science and Analytics Master of Science program.
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• DSA 8420: Adv Mathematical Programming

  3.00 Credits

  Clemson University

  
  Theory, methodology and applications of integer and nonlinear programming are covered. Topics include model development, computer solutions, branch and bound, unconstrained and constrained optimization algorithms, complexity and convergence analysis. Case studies in data science and analytics are included. Preq: Enrollment in the Data Science and Analytics Master of Science program and DSA 8280.
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