{"@id":"https://credentialengineregistry.org/resources/ce-8ecd1716-a469-4cf3-8ab4-5e9409898070","@type":"ceterms:MasterDegree","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-8ecd1716-a469-4cf3-8ab4-5e9409898070","ceterms:name":{"en-US":"M.S. in Computational Data Science"},"ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-99a51276-8e40-4f8f-a76e-696ad43e3903"],"ceterms:identifier":[{"@type":"ceterms:IdentifierValue","ceterms:identifierTypeName":{"en-US":"CHEDSS Program ID"},"ceterms:identifierValueCode":"60599"}],"ceterms:inLanguage":["en"],"ceterms:description":{"en-US":"The Master of Science degree in Computational Data Science is a Purdue University degree offered in the Department of Computer and Information Sciences. Data science is a cross between Computer Science and Statistics, and it involves data-driven knowledge discovery in terms of pattern analysis and prediction. You'll study statistics, regression, sequence analysis, machine learning, data mining, and data analysis (like database systems, information visualization, and \"big data\" analytics). Students graduate from this program ready to enter the workforce in the rapidly advancing field of data science, an interdisciplinary domain that cuts across computer science and statistics. You'll gain the skills necessary to ensure you are competitive in today's job market by gaining an understanding of theory, implementation (e.g., algorithms and appropriate computing languages), and the inherent \"nature\" of different data modalities, such as classification and prediction challenges on specific data (e.g., sparse and/or incomplete data)."},"ceterms:subjectWebpage":"https://science.indianapolis.iu.edu/iupui-cs/computational-data-science-iupui.html","ceterms:credentialStatusType":{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://credreg.net/ctdl/terms/CredentialStatus","ceterms:targetNode":"credentialStat:Active","ceterms:frameworkName":{"en-US":"Credential Status"},"ceterms:targetNodeName":{"en-US":"Active"},"ceterms:targetNodeDescription":{"en-US":"Awards of the credential are ongoing."}},"ceterms:learningDeliveryType":[{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://credreg.net/ctdl/terms/Delivery","ceterms:targetNode":"deliveryType:InPerson","ceterms:frameworkName":{"en-US":"Delivery Type"},"ceterms:targetNodeName":{"en-US":"In-Person Only"},"ceterms:targetNodeDescription":{"en-US":"Delivery is only face-to-face."}}],"ceterms:instructionalProgramType":[{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://nces.ed.gov/ipeds/cipcode/Default.aspx?y=56","ceterms:targetNode":"https://nces.ed.gov/ipeds/cipcode/cipdetail.aspx?y=56\u0026cip=30.3001","ceterms:codedNotation":"30.3001","ceterms:frameworkName":{"en-US":"Classification of Instructional Programs"},"ceterms:targetNodeName":{"en-US":"Computational Science"},"ceterms:targetNodeDescription":{"en-US":"A program that focuses on the study of scientific computing and its application.  Includes instruction in scientific visualization, multi-scale analysis, grid generation, data analysis, applied mathematics, numerical algorithms, high performance parallel computing, and numerical modeling and simulation with applications in science, engineering and other disciplines in which computation plays an integral role."}}]}