Computational methods in data science

  • Is computational science data science?

    Yet, the differences can be found in the focus of both: Computational sciences focuses on development of causal models rather than extracting patterns or knowledge from data by statistical models, while this is what Data Science is all about..

  • What are the computational aspects of data science?

    Computational Data Science combines aspects of statistics, computer science, mathematics and machine learning to identify trends, make predictions, and solve problems.
    Computational data science uses algorithms and data structures to store, manipulate, visualize and learn from large data sets..

  • What is the computational aspect of data science?

    Computational Data Science combines aspects of statistics, computer science, mathematics and machine learning to identify trends, make predictions, and solve problems.
    Computational data science uses algorithms and data structures to store, manipulate, visualize and learn from large data sets..

Elective Courses. Students must take 8 credit hours from graduate level elective courses in the areas of statistical modeling, data mining or database 
Example methods include linear and non-linear regression, neural networks, deep networks, convolutional neural networks, factor, tensorial and independent component analysis, sparsity inducing linear and non-linear regressions.
Yet, the differences can be found in the focus of both: Computational sciences focuses on development of causal models rather than extracting patterns or 

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