{"@id":"https://credentialengineregistry.org/resources/ce-ab6641ce-925e-44c8-881b-eed16a600b49","@type":"ceterms:MasterDegree","@context":"https://credreg.net/ctdl/schema/context/json","ceterms:ctid":"ce-ab6641ce-925e-44c8-881b-eed16a600b49","ceterms:name":{"en-US":"Analytics"},"ceterms:ownedBy":["https://credentialengineregistry.org/resources/ce-46728735-27f8-44dc-8f9d-3ce3ff0dfdf4"],"ceterms:offeredBy":["https://credentialengineregistry.org/resources/ce-46728735-27f8-44dc-8f9d-3ce3ff0dfdf4"],"ceterms:inLanguage":["en"],"ceterms:availableAt":[{"@type":"ceterms:Place","ceterms:name":{"en-US":"University of New Hampshire"},"ceterms:latitude":43.1359259,"ceterms:longitude":-70.9324341,"ceterms:postalCode":"03824","ceterms:addressRegion":{"en-US":"New Hampshire"},"ceterms:streetAddress":{"en-US":"105 Main Street"},"ceterms:addressCountry":{"en-US":"United States"},"ceterms:addressLocality":{"en-US":"Durham"}},{"@type":"ceterms:Place","ceterms:name":{"en-US":"University of New Hampshire at Manchester"},"ceterms:latitude":42.98714469999999,"ceterms:longitude":-71.4687566,"ceterms:postalCode":"03101","ceterms:addressRegion":{"en-US":"New Hampshire"},"ceterms:streetAddress":{"en-US":"88 Commercial Street"},"ceterms:addressCountry":{"en-US":"United States"},"ceterms:addressLocality":{"en-US":"Manchester"}},{"@type":"ceterms:Place","ceterms:name":{"en-US":"University of New Hampshire - Franklin Pierce School of Law"},"ceterms:latitude":43.207489,"ceterms:longitude":-71.5448541,"ceterms:postalCode":"03301","ceterms:addressRegion":{"en-US":"New Hampshire"},"ceterms:streetAddress":{"en-US":"2 White Street"},"ceterms:addressCountry":{"en-US":"United States"},"ceterms:addressLocality":{"en-US":"Concord"}}],"ceterms:description":{"en-US":"https://gradschool.unh.edu/analytics/program/ms/analytics (see: https://gradschool.unh.edu/analytics/program/ms/analytics)The curriculum for the one-­year interdisciplinary, full-­time M.S. in Analytics program begins in May on the Durham, NH campus. The 36-­credit program is comprised of ten core analytics and data science courses and two cluster electives. \n \n Electives can be taken in many areas of applied focus such as, but not limited to, health care, business, environmental sciences, sports management, and others.\n \n The program rests primarily on the coding languages of R and Python, but also SAS and SQL. Students receive training in a multitude of quantitative tools and algorithms such as machine learning and deep learning. They also get exposed to computational and analytic environments such as enterprise systems to streaming and distributed cloud systems. A sample of the module-based curriculum map, that stays relevant to changing technology may be seen here (see: https://d7admin.unh.edu/sites/default/files/departments/analytics_data_science/pdfs/2018_curriculum_map.pdf). \n \n The practicum courses are designed to instruct on two primary areas of content. One is to apply the core tools to a real-world project. The second is to provide useful exposure to the processes and professional development of the student in the role of analytics professional. Students will have the opportunity to learn methodologies such as LEAN and Agile project management. Students will also be exposed to conceptual mapping for data practitioners such as design thinking. They will do this both within projects should they or the host choose, or as added learning. View Practicum projects here (see: https://gradschool.unh.edu/analytics/about-analytics-data-science/practicum-projects).\n \n Flow of the MS in Analytics Program\n \n The Master of Science in Analytics begins each May. Each of the three semesters build in level of mastery. \n \n Summer (Beginner Analytics)\n \n The initial semester, brings together both the Graduate Certificate in Analytics (GCA) students and the M.S. students, to learn side by side. In the summer, students learn the basics of statistical and mathematical thinking, programming in three languages, and the foundations of data cleaning, visualization, and presentation. Each day, students will begin with instruction and spend the remainder of the day working on homework and project assignments, culminating in a team project around a social justice issue. In addition, a number of â€úsoft† skills are introduced such as LEAN project management and Agile training. And finally, students are exposed to a host of industry partners and perspectives on the rapidly changing world of analytics and data science through our guest speaker series.\n \n Fall and Spring (Intermediate and Advanced Analytics and Data Science)\n \n These semesters mirror one another, yet build in tools and applications. Students spend their mornings in class and in the afternoon collaborating in groups on projects, professional development and networking with industry partners/sponsors. Building on the knowledge gained in summer, they work toward the completion of the capstone practicum in spring. The Fall semester is spent on project scoping, background, data transfer, and understanding policies and procedures in place via the host or by the type of data being used. In Spring students are engaged in data mining, modelling and storytelling with outcomes for ultimate presentation back to the host site.\n \n Students will also receive opportunities to further develop professional skills and certifications around LEAN should they choose. \n \n Cluster Areas of Focus\n \n The Cluster Course electives consists of two required courses, taken in the fall and spring semesters. The final curriculum objective is to allow for specialization in a targeted area of student interest to provide students with a deeper knowledge in the subject area of their choice. Current cluster options include health, accounting, decision science, finance, marketing, economics, sports, human \u0026amp; technology interface, or self-designed focus.\n \n Key Program Highlights\n \n \n \n - Consists of 12 courses, 36 credit hours, 2 specialization electives\n \n - 1-year STEM masters or a 3-month certificate option\n \n - Gain expertise in advanced machine learning, text analytics, programming, visual analytics, and big data framework.\n \n - Curriculum stays relevant to the ever changing technology with an ability for the students to choose their specialization (i.e. Health/Business/Sports)\n \n - Students from diverse backgrounds - not just technical fields\n \n - Work hands-on, team-based learning"},"ceterms:occupationType":[{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://www.bls.gov/soc/","ceterms:targetNode":"https://www.onetonline.org/link/summary/11-1011.00","ceterms:codedNotation":"11-1011.00","ceterms:frameworkName":{"en-US":"Standard Occupational Classification"},"ceterms:targetNodeName":{"en-US":"Chief Executives"},"ceterms:targetNodeDescription":{"en-US":"Determine and formulate policies and provide overall direction of companies or private and public sector organizations within guidelines set up by a board of directors or similar governing body. 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Enact or oversee a corporate sustainability strategy."}},{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://www.bls.gov/soc/","ceterms:targetNode":"https://www.onetonline.org/link/summary/11-1021.00","ceterms:codedNotation":"11-1021.00","ceterms:frameworkName":{"en-US":"Standard Occupational Classification"},"ceterms:targetNodeName":{"en-US":"General and Operations Managers"},"ceterms:targetNodeDescription":{"en-US":"Plan, direct, or coordinate the operations of public or private sector organizations. Duties and responsibilities include formulating policies, managing daily operations, and planning the use of materials and human resources, but are too diverse and general in nature to be classified in any one functional area of management or administration, such as personnel, purchasing, or administrative services."}},{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://www.bls.gov/soc/","ceterms:targetNode":"https://www.onetonline.org/link/summary/15-2031.00","ceterms:codedNotation":"15-2031.00","ceterms:frameworkName":{"en-US":"Standard Occupational Classification"},"ceterms:targetNodeName":{"en-US":"Operations Research Analysts"},"ceterms:targetNodeDescription":{"en-US":"Formulate and apply mathematical modeling and other optimizing methods to develop and interpret information that assists management with decision making, policy formulation, or other managerial functions. May collect and analyze data and develop decision support software, service, or products. May develop and supply optimal time, cost, or logistics networks for program evaluation, review, or implementation."}},{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://www.bls.gov/soc/","ceterms:targetNode":"https://www.onetonline.org/link/summary/25-1011.00","ceterms:codedNotation":"25-1011.00","ceterms:frameworkName":{"en-US":"Standard Occupational Classification"},"ceterms:targetNodeName":{"en-US":"Business Teachers, Postsecondary"},"ceterms:targetNodeDescription":{"en-US":"Teach courses in business administration and management, such as accounting, finance, human resources, labor and industrial relations, marketing, and operations research. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research."}}],"ceterms:subjectWebpage":"https://catalog.unh.edu/graduate/programs-study/analytics/analytics-ms","ceterms:audienceLevelType":[{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"http://credreg.net/ctdl/terms/AudienceLevel","ceterms:targetNode":"audLevel:MastersDegreeLevel","ceterms:frameworkName":{"en-US":"AudienceLevel"},"ceterms:targetNodeName":{"en-US":"Masters Degree Level"}}],"ceterms:estimatedDuration":[{"@type":"ceterms:DurationProfile","ceterms:exactDuration":"P6Y"}],"ceterms:credentialStatusType":{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"http://credreg.net/ctdl/terms/CredentialStatus","ceterms:targetNode":"credentialStat:Active","ceterms:frameworkName":{"en-US":"CredentialStatus"},"ceterms:targetNodeName":{"en-US":"Active"}},"ceterms:instructionalProgramType":[{"@type":"ceterms:CredentialAlignmentObject","ceterms:framework":"https://nces.ed.gov/ipeds/cipcode/Default.aspx?y=55","ceterms:targetNode":"https://nces.ed.gov/ipeds/cipcode/cipdetail.aspx?y=55\u0026cip=52.1301","ceterms:codedNotation":"52.1301","ceterms:frameworkName":{"en-US":"Classification of Instructional Programs"},"ceterms:targetNodeName":{"en-US":"Management Science"},"ceterms:targetNodeDescription":{"en-US":"A general program that focuses on the application of statistical modeling, data warehousing, data mining, programming, forecasting and operations research techniques to the analysis of problems of business organization and performance. 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