introduction to computational thinking and data science pdf


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  • What is computational 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 computational thinking in data science?

    Occasionally referred to as algorithmic thinking, computational thinking is a systematic approach towards solving a complicated problem by breaking it down into smaller, simpler steps in a way that it can be executed by a computer or machine.7 mar. 2023

  • What is the introduction of computational thinking?

    In education, CT is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute.
    It involves automation of processes, but also using computing to explore, analyze, and understand processes (natural and artificial).

  • 4 Parts of Computational Thinking

    4 Parts of Computational Thinking

    Decomposition.
    The first step in computational thinking is decomposition. Pattern Recognition.
    Part of computational thinking is also pattern recognition. Abstraction.
    Abstraction is the process of extracting the most relevant information from each decomposed problem. Algorithmic Thinking.

Introduction to Computational Thinking and Data Science · Syllabus · Readings · Lecture Videos · Lecture Slides and Files · Assignments · Software  Autres questions
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