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  1. Data science

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    unstructured data. Data science is related to data mining, deep learning and big data. Data science is a "concept to unify statistics, data analysis, machine

  2. R (programming language)

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    RStudio, an integrated development environment, and Jupyter, a notebook interface. R is an implementation of the S programming language combined with

  3. Competitive programming

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    in competitive programming. These include: Participation in programming contests may increase student enthusiasm for computer science studies. The skills

  4. Computer programming

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    machine code of computer programs. These might be considered part of the programming process, but often the term software development is used for this larger

  5. Abstraction (computer science)

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    abstraction is removing irrelevant data so a program is easier to understand.[citation needed] Different programming languages provide different types

  6. Computer science

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    functions and avoids state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions or declarations

  7. End-user development

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    End-user development (EUD) or end-user programming (EUP) refers to activities and tools that allow end-users – people who are not professional software

  8. Data visualization

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    developed programs to meet the demand for learning data visualization and associated programming libraries, including free programs like The Data Incubator

  9. Big data

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    Application Programming Interfaces (APIs) provided by big data holders, such as Google and Twitter, to do research in the social and behavioral sciences. Often

  10. Computer science and engineering

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    algorithms, data structures, numerical analysis, machine learning, information theory, programming language theory and paradigms. The program aims at designing

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