{"@id":"https://credentialengineregistry.org/resources/ce-5b66f0ab-eb0c-40ea-a051-f91466ba171e","@type":"ceterms:MasterDegree","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-5b66f0ab-eb0c-40ea-a051-f91466ba171e","ceterms:name":{"en-US":"M.S. in Data Science"},"ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-5b250f35-7527-4115-9e5c-c49dd1dbed4e"],"ceterms:identifier":[{"@type":"ceterms:IdentifierValue","ceterms:identifierTypeName":{"en-US":"CHEDSS Program ID"},"ceterms:identifierValueCode":"61874"}],"ceterms:inLanguage":["en"],"ceterms:description":{"en-US":"Data Science is a rapidly growing and pivotal area within a number of different sectors and jobs.According to Forbes, data will continue to revolutionize various industries, with an expectedannual growth rate of 35% between 2024 and 2030. Meet the growing demand for data science experts with Purdue University's online Master of Science in Data Science. Delivered through an online and flexible modality, select different courses tailored towards your specific interest. Course topics include programming, data analysis, data engineering, data visualization, statistics, machine learning, natural language processing, and more."},"ceterms:subjectWebpage":"https://catalog.purdue.edu","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=30.7001","ceterms:codedNotation":"30.7001","ceterms:frameworkName":{"en-US":"Classification of Instructional Programs"},"ceterms:targetNodeName":{"en-US":"Data Science, General."},"ceterms:targetNodeDescription":{"en-US":"A program that focuses on the analysis of large scale data sources from the interdisciplinary perspectives of applied statistics, computer science, data storage, data representation, data modeling, mathematics, and statistics. Includes instruction in computer algorithms, computer programming, data management, data mining, information policy, information retrieval, mathematical modeling, quantitative analysis, statistics, trend spotting, and visual analytics."}}]}