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Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of completion. [57] [60] Other Coursera courses, projects, specializations, etc. cannot be audited—they are only available in paid versions ...
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.
A data science MOOC began in May 2013. [74] In May 2013, Coursera announced free e-books for some courses in partnership with Chegg, an online textbook-rental company. Students would use Chegg's e-reader, which limits copying and printing and could use the book only while enrolled in the class. [75]
Scientific Knowledge Graph aggregating, deduplicating, enriching metadata of publications, research data, research software, and other products, with citations links and links to funders and grants - core service in support of the European Open Science Cloud: Free OpenAIRE AMKE (not-for-profit) OpenAlex: Multidisciplinary: 205,000,000 [46]
LinkedIn Learning was founded as Lynda.com in 1995 in Ojai, California, as online support for the books and classes of Lynda Weinman, a special effects animator and multimedia professor who founded a digital arts school with her husband, artist Bruce Heavin.
CS50 (Computer Science 50) [a] is an introductory course on computer science taught at Harvard University by David J. Malan. The on-campus version of the course is Harvard's largest class with 800 students, 102 staff, and up to 2,200 participants in their regular hackathons .
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
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