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online application via hard copy, or in-person with a Saint Mary\u2019s admissions counselor, your application must include the following items:\nOfficial transcripts: An official transcript issued to Saint Mary\u2019s University of Minnesota from the institution posting the applicant\u2019s completed degree and other relevant transcripts documenting program prerequisites and potential transfer credits must be sent separately and directly from your institution. Saint Mary\u2019s University of Minnesota accepts official transcripts electronically from previously attended institutions. Transcripts should be sent to oladmissions@smumn.edu or mailed to:\nTranscript Processing Center\nSaint Mary\u2019s University of Minnesota\n851 Trafalgar Court, Suite 420\nMaitland, FL 32751\n \n\n                    ","description":"\n                    \n                    \n\n    Program Highlights\n        \n  \n\n\n    \n        \nDigital Badging for all Graduate Certificate Courses\nApply Graduate Certificate Credits to an Online M.S. in Business Intelligence and Data Analytics\nNo Letters of Recommendation Required\n\n    \n    \n\n        \n  \n\n\n    \n        Request Info        \n            \n        \n    \n\n    \n                ","hasCourse":[{"@type":"Course","@id":"https:\/\/www.smumn.edu\/degree\/graduate-certificate\/healthcare-analytics\/#Highlight20260320195826705-17953_0_EducationalOccupationalProgram_hasCourse_Course","name":"\n                          BIA 630 Data Analysis and Business Modeling (3 credits)                          \n                              \n                          \n                          \n                              \n                          \n                        ","description":"\n                      This course introduces advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. 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Students identify the proper use of complete regression, optimization, and exponential smoothing models.\nUpon completion of this course, students are expected to be able to do the following:\n\nUtilize datasets to develop statistics and probability to predict future outcomes\nImplement appropriate models needed to analyze and critically evaluate business objectives\nDevelop written and oral communication skills required to report on data-intensive business situations\nOrganize data-intensive content in a professional setting\nExecute advanced analytics techniques\n\n\n                    "},{"@type":"Course","@id":"https:\/\/www.smumn.edu\/degree\/graduate-certificate\/healthcare-analytics\/#Highlight20260320195826705-17953_1_EducationalOccupationalProgram_hasCourse_Course","name":"\n                          BIA 670 Data-Driven Culture (3 credits)                          \n                              \n                          \n                          \n                              \n                          \n                        ","description":"\n                      Examine ethical and legal considerations when working with healthcare data, including government regulations. 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Students study real world cases illustrating data governance in organizations, issues in patient privacy, data ownership, and restrictions on data analysis.\nUpon completion of this course, students are expected to be able to do the following:\n\nCompare the relationship between healthcare data collection laws and analytic needs\nEvaluate project needs to determine the level of sensitivity required in data set analysis\nExplain the ethical and legal considerations with healthcare data and consumer records\nAnalyze the needs that different organizations have with data governance\n\n\n                    "},{"@type":"Course","@id":"https:\/\/www.smumn.edu\/degree\/graduate-certificate\/healthcare-analytics\/#Highlight20260320195826705-17953_2_EducationalOccupationalProgram_hasCourse_Course","name":"\n                          BIA 671 Information Systems for Healthcare Analytics (3 credits)                          \n                              \n                          \n                          \n                              \n                          \n                        ","description":"\n                      This course explores performance management and technology management for the healthcare industry. 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