2021-2022 Catalog Update

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2021–2022CATALOGUPDATEUMGC.EDUThe University Made for You

MISSIONThe mission of University of MarylandGlobal Campus is improving the livesof adult learners. We will accomplishthis by operating as Maryland’s openuniversity, serving working adults,military servicemen and servicewomenand their families, and veterans whoreside in Maryland, across the UnitedStates, and around the world.VISIONUMGC will be a global leader in adulteducation focusing on career-relevantprograms that enable students torealize their professional aspirations.VALUESTable of ContentsSUMMARY OF CHANGESABOUT STUDY AT UMGC: ADMISSIONAdmission Procedures Students First: These are the peoplewho make our work possible.1 Accountability: We are eachresponsible for our overall success.2 Diversity: Each individual brings valueto our efforts and results. Integrity: Our principles andstandards are never compromised.Applicants to the Doctor of Management ProgramBACHELOR’S DEGREE PROGRAMS: CURRICULAData ScienceDOCTORAL DEGREE PROGRAMS: CURRICULACommunity College Policy and AdministrationCERTIFICATE PROGRAMS: UNDERGRADUATEBusiness Analytics356Public Safety Executive LeadershipCOURSE INFORMATIONUNDERGRADUATE COURSE DESCRIPTIONSComputer and Information ScienceCybersecurityData ScienceInformation Systems ManagementMathematicsPublic Safety AdministrationStatisticsGRADUATE COURSE DESCRIPTIONSCommunity College Policy and Administration Excellence: Quality is the hallmark ofour work. Innovation: We advance so otherscan benefit from our leadership. Respect: The rights and feelings ofothers are always considered. People Always: Our faculty and staffrepresent our differentiator andcompetitive advantage.7The following information is anupdate to the 2021–2022 UMGCcatalog and represents changesand additions made after originalpublication. Refer to the 2021–2022catalog for information on all otherprograms, services, and policies.

SUMMARY OF CHANGESThe following represent the policy and program changesmade to the 2021–2022 catalog since its publication: The Associate of Arts degree program is now available toapplicants with permanent and mailing addresses outsidethe state of Maryland, in addition to those populations listedon pp. 6 and 27 of the 2021–2022 catalog. Undergraduate students admitted in provisional status(described on p. 7 of the 2021–2022 catalog) are no longerlimited to enrolling in no more than 7 credits per semester.TABLE OF CONTENTS DATA 200 now satisfies the undergraduate general educationrequirement (described on pp. 28 and 42 of the 2021–2022catalog) in research and computing literacy for both the associate and bachelor’s degrees. The computer studies curriculum for the Associate of Arts(described on p. 32 of the 2021–2022 catalog) no longerrequires completion of CMIS 102 or a programming languagecourse. Also, DATA courses apply to the requirement for15 credits in computer-related coursework in addition tothe options already listed for this program. The eligibility requirements for federal student aid and mostUMGC assistance (listed on p. 308 of the 2021–2022 catalog)no longer include registering with Selective Service if requiredto do so or not being convicted for the possession or sale ofillegal drugs during the time you were receiving any type offederal financial aid. For the UMGC Completion Scholarship (described on p. 309of the 2021–2022 catalog), you must provide an official transcript showing a conferred associate degree from a Marylandcommunity college before the end of the second semester ofenrollment at UMGC. Additional annual maximum award limits and restrictionsmay apply to scholarships and grants (described on p. 309of the 2021–2022 catalog). Contact the Financial Aid Officefor details. An undergraduate major and minor in Data Science, an undergraduate certificate in Business Analytics, and a doctoral program in Community College Policy and Administration have beenadded; requirements for the undergraduate certificate in PublicSafety Executive Leadership have changed. Admission procedures for the doctoral program, program details for all the aforementioned programs, and related course descriptions follow.1C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

ABOUT STUDY AT UMGCAdmissionAdmission ProceduresApplicants to the Doctor of Management ProgramIf you are applying for admission to the DM program in community college policy and administration, you must submit thefollowing documentation along with your completed applicationbefore the posted deadlines: An official transcript documenting a master’s degree or moreadvanced credential An up-to-date résumé or curriculum vitae Two letters of recommendation from academic or professionalreferences, using the doctorate recommendation form availableat umgc.edu/dmccpaTABLE OF CONTENTS Responses to specific writing prompts (300–500 wordsper prompt)All applications are prescreened by doctoral program faculty andstaff based on the documentation submitted. If you pass the prescreen process, you are required to interview with the programadmissions committee, comprising faculty members, a staffmember, and the program director, who use a common interviewguide. Final recommendations for admission are based on evaluation of written submissions and interview recommendationsfrom faculty.Maryland residents are excluded from admission to the program.The complete admission file must be reviewed and accepted byUMGC before you can enroll in program coursework.2C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

BACHELOR’S DEGREE PROGRAMSCURRICULAData ScienceINDUSTRY CERTIFICATIONThis program is designed to help prepare you for the followingcertification exams, listed in alphabetical order:TABLE OF CONTENTSAVAILABLE SPRING 2022The following degree requirements and recommended curriculum apply to students who begin continuous study on or afterJanuary 1, 2022. AWS Certified Machine LearningMajor in Data Science Tableau Desktop SpecialistThe major in data science is designed to meet the growing needfor highly skilled professionals who can transform increasingamounts of data into actionable insights. The program provideshands-on experience with a number of the most frequently usedanalytical tools and methods, offering opportunities to manageand manipulate data; create data visualizations; build predictivemodels using different machine learning techniques; apply artificialintelligence (AI) and natural language processing techniques togain insights from free text, images, and videos; and make strategic data-driven recommendations that directly impact businessoutcomes. You’ll acquire fundamental knowledge and skills in datascience that will help you adapt to future changes in tools, technology, and the marketplace.Degree Requirements Microsoft Certified: Data Analyst Associate Tableau Desktop Certified AssociateBS IN DATA SCIENCECreditsGeneral Education Courses41Required Major Courses36Minor and Elective Courses43Total120What You’ll LearnREQUIRED MAJOR COURSES (36 CREDITS)Through your coursework, you will learn how toSTAT 200Introduction to Statistics (3) Communicate effectively orally and in writing, meeting expectations for content, purpose, organization, audience, and formatDATA 220Introduction to Data Analytics (3)DATA 300Foundations of Data Science (3) Implement all stages of data science methodology, includingdata extraction, data cleaning, data load, and transformation Execute best practices, using diverse technologies, in datascience, business intelligence, machine learning, and artificialintelligence Analyze social, global, and ethical issues and their implicationsas they relate to the use of existing and emerging data science,machine learning, and AI technologies Evaluate a business problem or opportunity to determine theextent data science can provide a viable solution and translatethe business problem into a viable project to meet organizational strategic and operational needs Incorporate data security, data privacy, and risk managementbest practices in the planning, development, and implementation of data science solutions Build and deploy the machine learning process throughout itslife cycle in full compliance with best practices for tool evaluation, model selection, and model validationIFSM 330Business Intelligence and Data Analytics (3)DATA 335Data Visualization (3)CSIA 300Cybersecurity for Leaders and Managers (3)DATA 430Foundations of Machine Learning (3)DATA 440Advanced Machine Learning (3)DATA 445Advanced Data Science (3)DATA 450Data Ethics (3)DATA 460Artificial Intelligence Solutions (3)DATA 495Data Science Capstone (3)RELATED REQUIRED COURSESNote: The following required courses may be applied to general educationor elective requirements.CMIS 102Introduction to Problem Solvingand Algorithm DesignMATH 140Calculus I Leverage big data analytics and AI technology to create solutions for stream analytics, text processing, natural languageunderstanding, AI, and cognitive applications3C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

BACHELOR’S DEGREE PROGRAMSCURRICULACourse SequencingThe following table is designed to provide an optimal order fortaking both required and recommended general education, major,and elective courses for this program. Your plan will be uniqueto you, based on your previous education. See pp. 41–43 of the2021–2022 catalog for information on general education andoverall requirements for completing a bachelor’s degree. Contactan advisor or a success coach if you have any questions aboutyour academic advisement report.Major and related requirements are listed in bold.TABLE OF CONTENTSBS IN DATA SCIENCERecommended and Required CoursesRequirement(s) FulfilledLIBS 150 Introduction toResearch (1)General education/computingand researchPACE 111T Program and CareerExploration in Technology (3)General education/computingand researchWRTG 111 Academic Writing I (3)General education/communicationsCMIS 102 Introduction to ProblemSolving and Algorithm Design (3)Related and general education/computingNUTR 100 Elements of Nutrition (3)General education/biological andphysical sciencesSTAT 200 Introduction toStatistics (3)MajorSPCH 100 Foundations of OralCommunication (3)General education/communicationsMATH 140 Calculus I (4)Related and general education/mathematicsWRTG 112 Academic Writing II (3)General education/communicationsDATA 220 Introduction toData Analytics (3)MajorHIST 125 TechnologicalTransformations (3)General education/arts andhumanitiesBIOL 103 Introduction to Biology (4)General education/biological andphysical sciencesBEHS 103 Technology inContemporary Society (3)General education/behavioral andsocial sciencesARTH 334 Understanding Movies (3)General education/arts andhumanitiesElective (3)ElectiveECON 103 Economics in theInformation Age (3)General education/behavioral andsocial sciencesDATA 300 Foundations ofData Science (3)MajorElective (3)ElectiveIFSM 330 Business Intelligenceand Data Analytics (3)Major4Elective (3)ElectiveDATA 335 Data Visualization (3)MajorElective (3)ElectiveCSIA 300 Cybersecurity for Leadersand Managers (3)MajorWRTG 393 Advanced TechnicalWriting (3)General education/communicationsElective (3)ElectiveDATA 430 Foundations of MachineLearning (3)MajorElective (3)ElectiveElective (3)ElectiveDATA 440 Advanced MachineLearning (3)MajorElective (3)ElectiveDATA 445 Advanced Data Science (3)MajorElective (3)ElectiveElective (3)ElectiveDATA 450 Data Ethics (3)MajorElective (3)ElectiveElective (3)ElectiveDATA 460 Artificial IntelligenceSolutions (3)MajorElective (3)ElectiveDATA 495 Data Science Capstone (3)Major/capstoneElective (3)ElectiveMinor in Data ScienceThe data science minor complements the skills you gain in yourmajor discipline by helping you develop specialized skills in indata science, business intelligence, machine learning, and artificial intelligence.Courses in the Minor (15 Credits)The minor in data science requires the completion of 15 creditsof coursework. STAT 200, IFSM 330, CSIA 300, and all DATAcourses apply.Courses already applied toward other degree requirements(e.g., major or general education) may not be applied toward theminor. At least 9 credits must be earned in upper-level courses(numbered 300 or above). Prerequisites apply for all courses.For a listing of all the requirements for the bachelor’s degree, referto your major in the 2021–2022 catalog.C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

DOCTORAL DEGREE PROGRAMSDEGREE REQUIREMENTS AND CURRICULUMDoctor of Management inCommunity College Policyand AdministrationAVAILABLE SPRING 2022The following degree requirements and recommended curriculum apply to students who begin continuous study on or afterJanuary 1, 2022.TABLE OF CONTENTSDesigned for college faculty and administrators who aspire tolead effectively and advance in administrative careers, the uniqueconcentration in community college policy and administrationoffers exceptional scholarship, intimate cohorts, online courses,short residencies, distinguished faculty, and dissertation supportin a program that can be completed within three yearsYou’ll work together in the same group of 15–20 studentsthroughout the entire program and build a virtual community,developed and led by current and former community collegepresidents and senior executives.ing and writing skills before entering this writing-intensive doctoralprogram. You are encouraged to take USCP 605, a noncreditcourse, to improve your writing skills.Degree RequirementsDM IN COMMUNITY COLLEGEPOLICY AND ADMINISTRATIONCreditsRequired Core Courses42Required Dissertation Courses12Total54Required Core CoursesCCPA 810ACCPA 810BLeadership and Change (3)Leadership and Change (3)CCPA 800ACCPA 800BFoundations of Management Theory (3)Foundations of Management Theory (3)CCPA 830ACCPA 830BResearch Methods (3)Research Methods (3)CCPA 821ACCPA 821BHigher Education Policy (3)Higher Education Policy (3)Note: Maryland residents are excluded from admission to the program.CCPA 841AWhat You’ll LearnCCPA 841BInstitutional Assessment in theCommunity College Environment (3)Institutional Assessment in theCommunity College Environment (3)With a highly respected credential, sophisticated knowledge, andan accomplished dissertation, you’ll emerge from the programwith the tools to transform student achievement and successfullyguide community colleges into the essential role they will play inthe future of higher education.Through your coursework, you will learn how to Lead transformational change in a rapidly changing sectorof higher education Advocate for the needs of community colleges and students atlocal, state, and federal levels Apply indicators of institutional effectiveness to all sectors ofcommunity college operations Apply theory and practice to continuously improve communitycollege policy and student outcomesPreparation Recommended for SuccessRecommendationsWe recommend work and prior management experience in acommunity college or other higher education institution or ingovernment or business. You need doctoral-level academic read-5CCPA 851ACCPA 851BCommunity College Advocacy, ResourceDevelopment, and Strategic Allocation (3)Community College Advocacy, ResourceDevelopment, and Strategic Allocation (3)CCPA 861ACCPA 861BSpecial Topics in Policy and Administration (3)Special Topics in Policy and Administration (3)CCPA 890Dissertation Part I (3)CCPA 891Dissertation Part II (3)CCPA 892Dissertation Part III (3)CCPA 893Dissertation Part IV (3)Course SequencingYou are expected to take 6 credits per term to progresswith your cohort. Program advisors will provide guidanceon course sequencing.C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

CERTIFICATE PROGRAMSUNDERGRADUATEBusiness AnalyticsAVAILABLE SPRING 2022The following degree requirements and recommended curriculum apply to students who begin continuous study on or afterJanuary 1, 2022.TABLE OF CONTENTSToday, employers are looking to hire professionals who possess data analytics skills and can inform and enhance decisionmaking within corporations, nonprofit organizations, governmentagencies, or the military. The certificate program in businessanalytics provides a valuable introduction to data science andcan enhance your career opportunities, regardless of your major.In this program, you learn how to manage and manipulate data,create data visualizations, and use cutting-edge technology togain insights from traditional and emerging data sources tomake strategic data-driven recommendations that influencemanagerial decision making and organizational outcomes.Overall certificate requirements are listed on p. 163 of the2021–2022 catalog.AN INTRODUCTORY COMPUTING COURSECHOSEN FROM THE FOLLOWING (3):Public SafetyExecutive LeadershipREVISED SPRING 2022The following degree requirements and recommended curriculum apply to all students currently pursuing the certificate andthose who begin continuous study on or after January 1, 2022.Develop the executive leadership skills needed to succeed in thepublic safety professional environment. There is currently a highdemand for leadership education for public safety officials at thefederal, state, and local governmental levels, as well as throughoutthe private sector. This certificate should be of professional benefitto both current and future public safety officials employed in publicsafety planning, public safety legal issues, public policy, publicsafety research and technology, and public safety leadership.Overall certificate requirements are listed on p. 163 of the2021–2022 catalog.SIX REQUIRED COURSES:PSAD 304Contemporary Public Safety Practices (3)PSAD 306Public Safety Planning (3)PSAD 408Public Safety Legal Issues and Public Policy (3)CMIS 102Introduction to Problem Solvingand Algorithm DesignIFSM 201Concepts and Applications ofInformation TechnologyPSAD 410Public Safety Research and Technology (3)PSAD 416Public Safety Leadership (3)Data Literacy FoundationsPSAD 414Public Safety Administration Ethics (3)DATA 200FOUR REQUIRED COURSES:STAT 200Introduction to Statistics (3)DATA 220Introduction to Data Analytics (3)IFSM 330Business Intelligence and Data Analytics (3)DATA 335Data Visualization (3)Total credits for certificate in Public Safety ExecutiveLeadership: 18AN UPPER-LEVEL COURSE CHOSEN FROMTHE FOLLOWING (3):CSIA 300Cybersecurity for Leaders and ManagersDATA 300Foundations of Data ScienceTotal credits for certificate in Business Analytics: 186C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

COURSE INFORMATIONUNDERGRADUATE COURSE DESCRIPTIONSComputer andInformation ScienceCMIS 102 Introduction to Problem Solvingand Algorithm Design (3)A study of techniques for finding solutions to problems throughstructured programming and step-wise refinement. The objectiveis to design programs using pseudocode and implement themin an appropriate programming language. Hands-on practice indebugging, testing, and documenting is provided. Topics includeprinciples of programming, the logic of constructing a computerprogram, and the practical aspects of integrating program modules into a cohesive application. Algorithms are used to demonstrate programming as an approach to problem solving.CybersecurityTABLE OF CONTENTSCSIA 300 Cybersecurity for Leaders and Managers (3)(Designed in part to help prepare for the EC-Council Secure Computer User [CSCU] certification.) Prerequisite: Any CMIS, CMSC,CMIT, CMST, CSIA, DATA, IFSM, or SDEV course. Recommended:IFSM 201. A survey of the cybersecurity principles, practices, andstrategies required by leaders and managers to become strategicpartners in the establishment, management, and governance of anenterprise’s cybersecurity program. The aim is to develop both anunderstanding of how cybersecurity supports key business goalsand objectives and the essential skills necessary for success in aleadership or managerial role. Topics include the fundamentals ofcybersecurity practices and principles; enterprise IT governanceprocesses and security controls; data security; the information lifecycle; intellectual property protections; privacy laws and regulations; security education, training, and awareness; and the needfor cooperation and collaboration between business units andthe organization’s cybersecurity program.Data ScienceDATA 220 Introduction to Data Analytics (3)Prerequisite: STAT 200. A practical introduction to the methodology, practices, and requirements of data science to ensure thatdata is relevant and properly manipulated to solve problemsand address a variety of real-world projects and business scenarios. Focus is on the foundational statistical concepts appliedto describing data sets with summary statistics, simple datavisualizations, statistical inference, and predictive analytics. Theobjective is to use data to draw conclusions about the underlyingpatterns that drive everyday problems through probability, hypothesis testing, and linear model building.7DATA 300 Foundations of Data Science (3)Prerequisites: CMIS 102 and DATA 220. An examination of the roleof data science within business and society. The goal is to identifya problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the businessproblem, build a model, and understand the feedback after modeldeployment. Emphasis is on the process of acquiring, cleaning,exploring, analyzing, and communicating data obtained from varietyof sources. Assignments require working with data in programminglanguages such as Python, wrangling data programmatically, andpreparing data for analysis using libraries like NumPy and Pandas.DATA 335 Data Visualization (3)Prerequisites: DATA 220 and IFSM 330. An overview of datavisualization principles in the context of business and data science. Focus is on visualization of different data types, includingtime-series, multidimensional data, dynamic tables, heatmaps,infographics, and dashboards. Hands-on projects require exploring data visually at multiple levels to find insights to create acompelling story and incorporating visual design best practicesto better communicate insights to the intended audience, such asbusiness stakeholders. Projects are selected from a wide range ofcontent areas such as retail, marketing, healthcare, government,basic sciences, and technology.DATA 430 Foundations of Machine Learning (3)Prerequisite: DATA 300. A hands-on introduction to machine learning principles and methods that can be applied to solve practicalproblems. Topics include supervised and unsupervised learning,especially linear regression, logistic regression, decision tree,naïve Bayes, and clustering analysis. Focus is on using data froma wide range of domains, such as healthcare, finance, marketing,and government, to build predictive models for informed decisionmaking. Discussion also covers handling missing data, performingcross-validation to avoid overtraining, evaluating classifiers, andmeasuring precision.DATA 440 Advanced Machine Learning (3)Prerequisites: DATA 430 and MATH 140. A project-based studyof advanced concepts and applications in machine learning(ML), such as neural networks, support vector machines (SVM),ensemble models, deep learning, and reinforced learning. Emphasis is on building predictive models for practical business andsocial problems, developing complex and explainable predictivemodels, assessing classifiers, and comparing their performance.All stages of the machine learning life cycles are developed, following industry best practices for selecting methods and tools tobuild ML models, including AutoML.C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

COURSE INFORMATIONUNDERGRADUATE COURSE DESCRIPTIONSDATA 445 Advanced Data Science (3)Prerequisites: DATA 335 and DATA 430. A project-based introduction to the concepts, approaches, techniques, and technologies formanaging and analyzing large data sets in support of improveddecision making. Activities include using technologies such asSpark, Hive, Pig, Kafka, Hadoop, HBase, Flume, Cassandra, cloudanalytics, container architectures, and streaming real-time platforms. Discussion covers how to identify the kinds of analysesto use with big data and how to interpret the results.DATA 450 Data Ethics (3)TABLE OF CONTENTSPrerequisite: DATA 430. Recommended: CSIA 300. A study ofethics within the context of data science, machine learning, andartificial intelligence. Emphasis is on examining data and modelbias; building explainable, fair, trustable, and accurate predictivemodeling systems; and reporting responsible results. Topicsinclude the technology implications of human-centered machinelearning and artificial intelligence on decision making in organizations and government and the broader impact on society, including multinational and global effects.DATA 460 Artificial Intelligence Solutions (3)(Designed to help prepare for the AWS Certified Machine Learningor Microsoft Designing and Implementing an Azure AI Solutionexam.) Prerequisite: DATA 430. A hands-on, project-based studyof artificial intelligence and machine learning solutions to complexproblems. Topics include natural language processing, computervision, and speech recognition.DATA 495 Data Science Capstone (3)Prerequisites: DATA 440, DATA 445, and DATA 450. A projectbased, practical application of the knowledge, technical skills, andcritical thinking skills acquired during previous study designedto showcase the student’s data science expertise. Individuallyselected projects include all phases of machine learning lifecycles and a peer-reviewed final report and presentation. Topicsare selected from student-affiliated organizations or employers,special government/private agency requests, or other facultyapproved sources in a wide range of domains, such as healthcare,financial services, marketing, sciences, and government.8Information SystemsManagementIFSM 330 Business Intelligence and Data Analytics (3)Recommended: IFSM 201 or IFSM 300. A hands-on, project-basedintroduction to databases, business intelligence, and data analytics.The aim is to design secure industry-standard databases and utilizebusiness intelligence and data analytics techniques and technologies to support decision making. Topics include data and relationaldatabases, SQL queries, business intelligence tools and alignmentwith business strategy, data analytics, and visualization techniques.MathematicsMATH 140 Calculus I (4)Prerequisite: MATH 108 or MATH 115. An introduction to calculus.The goal is to demonstrate fluency in the language of calculus;discuss mathematical ideas appropriately; and solve problems byidentifying, representing, and modeling functional relationships.Topics include functions, the sketching of graphs of functions,limits, continuity, derivatives and applications of the derivative,definite and indefinite integrals, and calculation of area.Public SafetyAdministrationPSAD 304 Contemporary Public Safety Practices (3)Recommended: PSAD 302. An investigation of contemporarystrategic public safety practices. The goal is to apply the concepts of hazard and risk identification and management, qualitycontrol methodology, customer service, integrated public safetyservices, and public and private partnerships to public serviceadministration decision making. Discussion covers hazard andrisk analysis, customer service awareness (including expectationsand demands), quality control methodology (including industrystandards and accreditation), integrated public services, bestpractices, and public/private partnerships.C ATA LO G U P DAT E 20 21–20 2 2u m g c .e d u /p r o g r a m s

COURSE INFORMATIONUNDERGRADUATE COURSE DESCRIPTIONSPSAD 306 Public Safety Planning (3)PSAD 416 Public Safety Leadership (3)Recommended: PSAD 304. An examination of strategic andoperational planning in public safety administration. The aim is toidentify and analyze an existing organizational strategic plan thatincludes budgeting and resource allocation, identify and analyzean existing operational plan, and identify the process for implementation of operational plans. Topics include strategic plans,budgeting, resource allocation, operational plans, hazard mitigation plans, emergency operation plans, incident action plans, andimplementation, including positive and negative forces.Recommended: PSAD 304. A study of leadership theories, skills,and techniques used in public safety administration. The objective is to define and explain basic concepts of leadership; analyzepersonal leadership knowledge, skills, and abilities; and evaluateleadership performance in the current public safety environment.Topics include leadership, leadership theories and styles, leadership roles, leadership performance, individual leadership skills andplans, effective leadership, and future trends.PSAD 408 Public Safety Legal Issues and Public Policy (3)TABLE OF CONTENTSRecommended: PSAD 304. A study of the legal and public policyissues faced by public safety administrators. The objective is todescribe the legal system; the legal and political environment;administrative laws and regulations for the work environment; andthe interrelationship among law, regulations, and public policy.Topics include the federal, state, and local legal systems; the legaland political environment; workplace administrative laws andregulations; public policy; liability; and risk reduction.PSAD 410 Public Safety Research and Technology (3)Recommended: PSAD 304. An examination of research and technology applications in public safety administration. The goal isto describe the principles of scientific research; evaluate existingresearch and technology; and apply the methods and resources ofresearch, science, and technology to public safety administration.Topics include scientific research, research methodology, technology, and evaluating and utilizing research and technology in publ

Cybersecurity . update to the 2021-2022 UMGC . Data Science . . Leverage big data analytics and AI technology to create solu-tions for stream analytics, text processing, natural language . IFSM 330 Business Intelligence and Data Analytics (3) DATA 335 . Data Visualization (3) CSIA 300 . Cybersecurity for Leaders and Managers (3)

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