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  2. Harvard John A. Paulson School of Engineering and Applied ...

    en.wikipedia.org/wiki/Harvard_John_A._Paulson...

    At the graduate level, the School offers master's and PhD degrees in areas including applied mathematics, applied physics, bioengineering, data science, chemical engineering, computational science and engineering, computer science, electrical engineering, design engineering, applied computation, environmental science and engineering, as well as ...

  3. Master in Data Science - Wikipedia

    en.wikipedia.org/wiki/Master_in_Data_Science

    A Master of Science in Data Science is an interdisciplinary degree program designed to provide studies in scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, [1] [2] similar to data mining.

  4. List of master's degrees - Wikipedia

    en.wikipedia.org/wiki/List_of_master's_degrees

    This is a list of master's degrees; ... Master of Data Science; Master of Defence Administration; ... Master of Science in Engineering;

  5. List of master's degrees in North America - Wikipedia

    en.wikipedia.org/wiki/List_of_master's_degrees_in...

    Master in Interdisciplinary Data Science, the University of Michigan School of Information's Master of Applied Data Science (MADS), and Master of Information and Data Science (MIDS) are professional graduate degrees in Data Science designed to help meet the need for knowledgeable data scientists who can answer important questions with data ...

  6. UC Berkeley School of Information - Wikipedia

    en.wikipedia.org/wiki/UC_Berkeley_School_of...

    The Master of Information and Data Science (MIDS) program is a Masters program that trains data science professionals and managers. The MIDS program is distinguished by its disciplinary breadth with course requirements including research design, ethics and privacy, data visualization, along with data engineering, machine learning, and statistical analyses.

  7. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    Data engineering refers to the building of systems to enable the collection and usage of data. This data is usually used to enable subsequent analysis and data science, which often involves machine learning. [1] [2] Making the data usable usually involves substantial compute and storage, as well as data processing.

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