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A Master of Science in Information Technology (abbreviated M.Sc.IT, MScIT or MSIT) is a master's degree in the field of information technology awarded by universities in many countries or a person holding such a degree. The MSIT degree is designed for those managing information technology, especially the information systems development process.
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.
The Master of Science (MSc) degree is a program officially recognized by the Spanish Ministry of Education. It usually involves 1 or 2 years of full-time study. It is targeted at pre-experience candidates who have recently finished their undergraduate studies. An MSc degree can be awarded in every field of study.
A Master of Science degree conferred by Columbia University, US. A master's degree [note 1] (from Latin magister) is a postgraduate academic degree awarded by universities or colleges upon completion of a course of study demonstrating mastery or a high-order overview of a specific field of study or area of professional practice. [1]
CSIR-UGC NET – All India test for entrance into Science Ph.D. programs and for eligibility to teach at undergraduate level across India. Having qualification as a lectureship from CSIR-UGC NET is compulsory for teaching across Indian colleges and universities at undergraduate and postgraduate level.
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]
Don't rely on bloviating pundits to tell you who'll prevail on Hollywood's big night. The Huffington Post crunched the stats on every Oscar nominee of the past 30 years to produce a scientific metric for predicting the winners at the 2013 Academy Awards.
It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the counterpart of principal component analysis for categorical data. [citation needed] MCA can be viewed as an extension of simple correspondence analysis (CA) in that it is applicable to a large set of categorical variables.