Random Matrix Theory in Data Science and Statistics
Johns Hopkins University · MD · EN.553.796
Random Matrix Theory in Data Science and Statistics is a subject at Johns Hopkins University, MD. It covers topics like data-mining, data-science, statistical-computing, statistical-learning. It is part of 1 degree. The information below is compiled from public course material — approximate, not official.
Johns Hopkins University
EN.553.796
3.00
Topics covered
Degrees that include Random Matrix Theory in Data Science and Statistics
Frequently asked questions
What is Random Matrix Theory in Data Science and Statistics about?
Random Matrix Theory in Data Science and Statistics covers topics like data-mining, data-science, statistical-computing, statistical-learning.
Which degrees include Random Matrix Theory in Data Science and Statistics?
Random Matrix Theory in Data Science and Statistics is part of 1 degree, including Applied Mathematics and Statistics, Master of Science in Engineering.
How many credit points is Random Matrix Theory in Data Science and Statistics?
Random Matrix Theory in Data Science and Statistics at Johns Hopkins University is typically around 3.00 credit points. Approximate — confirm with the university.
Where is Random Matrix Theory in Data Science and Statistics taught?
Random Matrix Theory in Data Science and Statistics is taught at Johns Hopkins University, MD.
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Sources: Johns Hopkins University public course catalogue. Information is compiled and summarised — not copied verbatim — and is approximate; always confirm with the original source.
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