Technology Management
Technology Management (TECH MGMT MS)
33 Credits
MASTER OF SCIENCE • 33 CREDITS • TECH MGMT MS
Program Description
The objective of the Master of Science in Technology Management is to offer a high quality, interdisciplinary technical and business graduate curriculum in technology management for today’s organizations. This program is designed to prepare graduates for a life-long career addressing critical leadership roles in private, public or government organizations. The MS in Technology Management combines a set of business and technical competencies to give Davenport University graduates the competitive advantages needed to lead information technology departments in the global economy.
Curriculum
Students will apply leadership tactics, basic observational methods and logical reasoning to demonstrate best practices in problem solving with foundational knowledge in the following areas: industry regulations, network technologies, product and project management, risk mitigation, business continuity, information technology disaster recovery, total quality management, budgeting and return on investment by using appropriate tools, methods and applications. Students will also choose electives based on their career focus and complete a thesis under the direct guidance of a faculty member.
The elective courses will provide an introduction to the different technical and administrative aspects of Technology Management. Topics will include: wireless networks, accounting information systems, banking and financial security, as well as leadership and change management strategies.
Foundational Knowledge Requirements
All students admitted into the Davenport University Master of Science in Technology Management are expected to have the necessary undergraduate preparation, as outlined in the Admissions Requirements, prior to entering the 600-level courses. Students who have not successfully completed equivalent undergraduate courses will be required to complete the following graduate (500-level) foundational courses or the undergraduate level equivalent courses. A grade of “B” or better must be earned in each course to show proficiency.
Foundational Knowledge Courses
- IAAS 581 - Information Security and Assurance
- STAT 500 - Statistics for Business
MASTER’S THESIS
A thesis paper forms the capstone of this Master of Science in Technology Management program. The capstone is a comprehensive research paper encompassing the learning from the students’ coursework in the program, and is to be completed under the guidance of your faculty advisor and/or university designated faculty member . Prior to enrolling in CAPS 798 - Technology Management Thesis, students must have both an approved Capstone Intent Form and an approved Research Proposal on file with the Program Director.
More details on the master’s thesis and capstone process may be found in the Capstone Guidebook available from your faculty advisor.
NOTE: PMP®, PgMP®, CAPM®, PMI-SP®, PMI-RMP®, and PMI-ACP® are registered marks of the Project Management Institute, Inc.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
24 Credits | |
|---|---|---|
| CISP600 | This course reviews the major content areas of information systems management that will be examined at various organizational levels of MS Technology Management. The major content areas (IT domains) to be covered include information technology management, networking, Web, database, programming and systems development. Upon completion of this course, students will be prepared to analyze, define, and research the unique management considerations of each domain within various organization levels. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| FINC610 | This course applies finance concepts to evaluate and manage budgets in financial decision making in the global environment. The course will include a foundational knowledge of accounting principles such as budget development and execution, program initiation, cost and revenue estimation, budget strategy and evaluation. Students will prepare a plan to obtain funding and manage a project or department budget. Basic financial concepts are covered such as capital budgeting, working capital management, risk and return measurement, cost classification, debt and equity financing and cash flow analysis. Students should be familiar with Microsoft Excel. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| GPMT630 | This course covers the fundamental concepts and applied techniques for cost effective management of both long-term programs and short-term projects. The content deals with planning, scheduling, organizing, and controlling projects using agile methodology for software development. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS600 | This course is a comprehensive study of the techniques used to protect information infrastructure and assets, with a primary focus on the Defense In Depth model that emphasizes the role of people, process and technology. Topics include security problems in computing, networks and distributed systems, and the criticality of the CIA triad; confidentiality, integrity and availability of technology-based resources. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Required undergraduate or 500+ level prerequisite courses | |
| IAAS667 | This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| STAT615 | This course explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. The course will also survey decision making and making recommendations using qualitative and quantitative data. Students will also discover threats to internal and external validity for quantitative research. Minitab will be used throughout the course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Completion of an undergraduate course in introductory statistics (STAT220) course or STAT500 | |
| TMGT685 | Upon completion of this course students will be prepared to incorporate the strategies and processes of different leadership models and organizational change into their personal leadership plan. Students will explore the leader’s role during technological changes and best approaches to lead and manage these changes within the organization. The course will survey how transformational leadership can be applied to foster innovation, technological change, examine the relationships between developing enterprise level, innovative strategies and performing in the role of a transformational CIO leader. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| TMGT788 | This course on statistics explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. Note: This class is preparatory to beginning the Technology Management Thesis and should be completed, at minimum, the semester prior to registration for CAPS798. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): STAT615 |
Elective Courses - Select two (2) of the following: |
6 Credits | |
|---|---|---|
| GPMT699 | This course prepares students for the Project Management Professional (PMP)® certification exam developed and conducted by the Project Management Institute (PMI). This PMI® Authorized PMP® Exam Prep course provides a focused review of subject matter for the current exam and includes PMI-developed course content. Note: Successful completion of this preparatory course does not guarantee passing the exam. In addition, to sit for certification exams, students must meet educational and work experience requirements. Please refer to www.pmi.org for specific exam requirements. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): GPMT287 or equivalent experience. NOTE: PMP®, Project Management Professional (PMP)®, PMBOK® and PMI® are registered marks of the Project Management Institute, Inc. | |
| TMGT655 | This course surveys the technical and managerial challenges of leading innovation in high-tech enterprises and industries. Particular consideration is given to the forces affecting the nature and rate of technological innovation and the managerial alternatives available to both established and entrepreneurial organizations. The course explores sources of innovation, including acquisitions and alliances, real options thinking for investing under uncertainty, managing new ventures and developing effective processes and organizational structures for driving sustainable results. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): CISP600 | |
| TMGT750 | This course explores the thinking processes CIO’s use when solving IT problems, making decisions, formulating IT strategies, and executing IT strategic plan. This course will survey CIO’s best practices and current industry standards. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT655 and TMGT685 |
Capstone |
3 Credits | |
|---|---|---|
| CAPS798 | A thesis project forms the capstone of this Master of Science program. In order to register, a student must complete all course requirements for this degree and submit an acceptable proposal to the technology management faculty for approval via a capstone intent form. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT788, last semester; Technology Core Courses and Management and Leadership Core Courses completed. |
Master of Science in Health Informatics and Information Management
Master of Science in Health Informatics and Information Management (HIIM MS)
33 Credits
MASTER OF SCIENCE IN HEALTH INFORMATICS AND INFORMATION MANAGEMENT • 33 CREDITS • HIIM MS
Davenport University’s Master of Science in Health Informatics and Information Management is an interdisciplinary program providing a unique blend of business, technology and health care graduate education for current health system environments. Today’s health information management professionals are hybrids who work closely with technology professionals, management professionals and health care providers to ensure the integrity, confidentiality, and appropriate access of health care information. Reflecting the most contemporary practices in the field, the program is structured to provide multiple perspectives in the development, implementation, and maintenance of information and data systems, data analysis, privacy and security, as well as strategic and operational resource policy and planning. This interdisciplinary program prepares graduates to perform and lead activities related to access, protection, and implementation of systems to analyze and leverage health information into business intelligence for improved decisionmaking in the information-driven, knowledge-based environment. Students may select from the basic Master’s degree at 33 credit hours, or may also obtain a Data Analytics Certificate by taking two additional courses.
Health Informatics and Information Management Foundational Knowledge Requirements
When accepted, a student may be required to complete up to three additional courses if the student’s previous academic experiences do not display they have successfully completed courses focused on Anatomy & Physiology, Pathophysiology, and/or Medical Terminology. These courses can be completed in conjunction with the program’s core courses but must be completed before the student’s final semester.
Students who have not successfully completed equivalent undergraduate courses, outlined in the Admissions Requirements, will be required to complete the following graduate foundational courses or the undergraduate level equivalent courses before taking 600-level courses. A grade of “C” or better must be earned in each foundational course to show proficiency.
Foundational Knowledge Courses:
- CISP 547 - Database Design
- IAAS 581 - Information Security and Assurance
- HINT 570 - Clinical Vocabulary and Health Records
- STAT 500 - Statistics for Business
The two Data Analytics courses taken as requirements within the Master of Science in Health Informatics and Information Management and they may also be used as part of a Graduate Certificate in Data Analytics or as part of the Master of Science in Data Analytics
Which class should I take? When should I take it?
See our Recommended Program Sequences:
- Health Informatics and Information Management, MS (web)
- Health Informatics and Information Management, MS (pdf)
Courses |
30 Credits | |
|---|---|---|
| DATA610 | Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA667 | Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HCMG630 | This course provides a systematic overview of the U.S. Healthcare Delivery System. Students will examine key components involved in the delivery and provision of healthcare services, including cultural diversity. This course also provides students an opportunity to examine the origin, development, structure, organization, and operational issues as they relate to hospitals and healthcare delivery systems. Note: A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HCMG750 | The focus of this course is to provide a working knowledge of payment policies and reimbursement methodologies used in health care and how they vary by payment source (governmental, private, and capitated insurance). Methodologies used by facilities and practitioners will be applied and compared. Factors affecting payment will be discussed. Costing methodologies, revenue cycle management, purchasing strategies, budgeting, and variance analysis applied to health care are examined. Note: A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): HCMG630 | |
| HINT601 | This seminar is required in the first semester of acceptance to the College of Health Professions Health Informatics and Information Management program. The program expectations and the HIIM Student Handbook will be reviewed. Students in this course must register and complete the required Criminal Background Check (CBC) and Drug Screen (DS). Note: This course is graded on a Pass/Fail basis. If the CBC/DS portion of the class is not completed in the specified time frame, a failing grade will be given for the course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HINT730 | This course will provide an overview of the legal processes and compliance issues related to health data. Students will review HIPAA compliance requirements as well as review risk management strategies and policies. Students will develop a training program related to legal issues and compliance and incorporate project management methodologies. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HINT760 | This course provides an introduction to research study design, methods, descriptive and inferential statistics needed to conduct research studies in the health information management domains. Topics include institutional review boards, ethics in research, the research process, data collection and presentation of data. Students will establish the framework for their capstone thesis/project. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| HINT775 | Students in this course will explore the concepts of information governance. Data management policies will be evaluated to ensure they are compliant with federal and state regulations. The course will discuss managing information while supporting the organization’s strategy, operations and risk requirements. Students will review and evaluate the processes needed in today's e-health environment related to information interoperability. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS600 | This course is a comprehensive study of the techniques used to protect information infrastructure and assets, with a primary focus on the Defense In Depth model that emphasizes the role of people, process and technology. Topics include security problems in computing, networks and distributed systems, and the criticality of the CIA triad; confidentiality, integrity and availability of technology-based resources. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Required undergraduate or 500+ level prerequisite courses | |
| IAAS675 | This course will provide the framework for developing and integrating security, critical infrastructures and assets prevalent in the healthcare and hospital industries. Legislation, policies, and case studies specific to the healthcare services field will be highlighted. Topics will include risks and vulnerabilities, security safeguards and standards, access control, audits, disaster recovery planning, security policy and procedures, and physical and logical security systems. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| MGMT653 | This course is designed to provide new ways of thinking about leadership philosophies and strategies to influence the behaviors of individuals and groups in organizations. Students begin with an exploration of the nature of effective leadership and leadership theories. Understanding power, creating change, developing teams, and guiding group decisions are examined in the context of the roles of a leader. Students learn how to recognize leadership traits and approaches so they can develop their own leadership style. Case studies involving real-world situations that confront leaders are used so that students can formulate strategies to improve the performance of followers through effective leadership. A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): BUSN520 |
Capstone |
3 Credits | |
|---|---|---|
| HINT799 | A thesis or project is required for the capstone in the HIIM program. In order to register, a student must have completed all course requirements for this degree and submit an acceptable proposal to the HIIM Program Director. The thesis consists of original research on any topic in the area of health information management, health information systems and/or health informatics. Oral presentation and defense of the thesis is required. The capstone project will be a rigorous project focused on a real-world health information, health information systems or health informatics setting and application of problem-solving methods for development of solutions. A final written report is required. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): All HIIM MS courses; Program Director Approval; must be taken in last semester. |
Master of Science in Data Analytics
Master of Science in Data Analytics (DATANLYTC MS)
30 Credits
MASTER OF SCIENCE IN DATA ANALYTICS • 30 CREDITS • DATANLYTC MS
Data Analytics is used to analyze vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. All aspects of the business and medical communities, as well as government agencies and non-profit organizations, rely on data analytics, yet are hampered by a growing shortage of data analysts. Davenport’s 30 credit hour Master of Science in Data Analytics responds to this need. The degree is delivered jointly by the College of Arts and Sciences in partnership with the Colleges of Technology, Business and Health Professions. The program is online and prepares individuals to conduct sophisticated analysis of existing data and create new data systems and methodologies. It is also designed to enable these individuals to make recommendations that increase effective use of data to help organizations meet specific goals and respond to new opportunities. The program uses industry standard software in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Course progression and content is carefully formulated to build competency in data analysis for students from a broad range of disciplines and experiences, including those who are new to the field.
DATA courses are only offered in a 15-week online format.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
12 Credits | |
|---|---|---|
| DATA610 | Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA625 | This course introduces students to data mining methods and applications. It covers basic concepts and tools for data mining, including data sources, data cleaning tools and methods, mainstream algorithms for data mining, statistical modeling, popular tools for mining structured data and unstructured data. Students will also learn how data mining can be effectively used in various application areas to drive decisions and actions. Students get hands-on practice by conducting a data analytics project using real world data sets. | |
| DATA667 | Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA710 | R programming language concepts are covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples. Upon completing this course, students will be able to employ advanced modeling techniques to write R code to conduct data analysis with strong reusability. |
Advanced Courses |
15 Credits | |
|---|---|---|
| DATA728 | This course will be a more advanced treatment of data mining and predictive analytics concepts introduced in DATA625 with a focus on customer relationship management (CRM). Using customized variations of the industry-standard CRISP-DM methodology, it will provide an experiential learning opportunity to explore all six phases of the model. This includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Industry standard tools and techniques are utilized to prepare students with the knowledge to be successful in current organizations. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA625 | |
| DATA742 | Students will be introduced to the concept of the data warehouse and the role it plays in an organization’s overall business intelligence and analytics strategy. This course will cover the two predominate warehouse design strategies, as well as hybrid designs that combine best practices from both areas, including the requirements of a data warehouse, selecting the proper design strategy, choosing the proper tools to support that design, selecting metrics for monitoring performance, data quality, and planning future enhancements. Students will be able to build a high-level plan for implementing a data warehouse in their organization or planning future changes to an existing warehouse if present. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA758 or DATA790 | Essentials of Cloud Computing or Data Analytics Internship | 3 |
| DATA772 | This course covers statistical procedures used in data analytics with emphasis on hands-on practice. Industry standard software is used to import and prepare data for model development as well as for developing various types of regression models. Assessment of model performance and methods for model selection are also covered. Emphasis is also placed on parameter estimation, variable selection, and diagnostic checking of these models and their use for statistical inference and prediction. Both numerical and graphical techniques are used for diagnostics and reporting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA710 | |
| DATA785 | This course covers statistical modeling in the use of statistical methods to develop models that can be used for predicting future numerical or categorical outcomes in processes for disciplines ranging from business to science. The philosophy of modeling as well as common modeling methods and model adequacy assessment procedures are covered. Industry standard software is used to prepare data, develop and assess models, obtain predictions, and present results. The main thrust of the course is on the application of predictive modeling rather than the theory behind it. Selected projects will be used to provide hands-on experience with the various steps involved in modeling and predicting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA772 |
Capstone Project |
3 Credits | |
|---|---|---|
| DATA792 | Students will apply all of their theoretical and practical experience to design and execute an analytics project on a chosen topic as a culmination of their analytics program, thereby demonstrating competency of program learning outcomes. Students will select the techniques to be used in the study, collect and analyze data for the purpose of drawing conclusions and making recommendations to the decision makers of an organization. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Course may only be elected in the final semester of the program. |
Computer Science
Computer Science (COMP SCIE MS)
30 Credits
MASTER OF SCIENCE • 30 CREDITS • COMP SCIE MS
The Master Program in computer science emphasizes software development, theoretical foundations of computer science and cyber security. It is designed to prepare students for professional positions in industry, government and business, and to provide preparation for graduate work at the doctoral level.
Foundational Knowledge Requirements:
All students admitted into the Davenport University Master of Science in Computer Science are expected to have the necessary undergraduate preparation, as outlined in the Admissions Requirements, prior to entering the 600-level courses. Students without a BS in Computer Science may need to complete the following courses before beginning 600-level courses:
- CSCI 531 - Introduction to Programming
- CSCI 534 - Object Oriented Programming with C#
- CSCI 545 - Data Structures and Algorithms
- MATH 515 - Calculus I
Which class should I take? When should I take it?
See our Recommended Program Sequences:
- Computer Science, MS - Concentration: Computer Science (web)
- Computer Science, MS - Concentration: Computer Science (pdf)
- Computer Science, MS - Concentration: Security (web)
- Computer Science, MS - Concentration: Security (pdf)
Core Courses |
18 Credits | |
|---|---|---|
| CSCI635 | General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture, bootloader, device drivers and I/O. Advanced topics may include: processes and threads, CPU scheduling; process synchronization; deadlock, threads, memory management; cache; main memory; virtual memory; virtual machine; shared-memory and message-passing based parallelism; clusters; database concepts; security and protection; authentication; and cloud computing. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI655 | The study of the principles, designs, implementations, performance and security issues and areas of current research in computer networks. This may include various types of computer buses, local area networks, long haul networks and layered network models. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI672 | This course covers the theory of computer science emphasizing automata, grammars computation and their applications in the specification of languages and computer systems, models of computation and complexity. Finite-state machines, pushdown automata, Turing machines, regular expressions, decidability, computational complexity, including classes P, NP, NP-complete, NP-hard, and PSPACE will be explored. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI728 | This course will study the design and analysis of algorithms, their correctness, their limitations and their relationship to other algorithms. Students will learn how to analyze a problem and determine its reducibility to a common problem with a current solution. Topics covered may also include Computational Geometry, NP-Completeness, Approximation Algorithms, Dynamic Programming, Greedy Algorithms and Reductions. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. |
Thesis/Project (More details on the Master Research Thesis or Master Project may be found in the Capstone Guidebook available from your faculty advisor) |
(6) Credits | |
|---|---|---|
| CSCI794 or CSCI798 | Master Project or Master Research Thesis | 6 |
Choose one of the following Concentrations: |
12 Credits |
|---|
Computer Science Concentration [CSCC] |
(12) Credits | |
|---|---|---|
| CSCI678 | This course will look at algorithms and concepts that are popular in the artificial intelligence field. Topics covered may include knowledge representation, constraint satisfaction problems, classical search, adversarial search, probabilistic reasoning, reinforcement learning, and robotics. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI744 | This course will look at the algorithms and concepts that are popular in the fields of data mining and machine learning. Topics covered may include deep learning, convolutional neural networks, linear and nonlinear models for classification, kernel methods, support vector machines and dimensionality reduction techniques. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI756 | This course will look at current research progress and trends in the Computer Vision field. Topics covered may include scene analysis, object detection and tracking, segmentation, texture and texture based recognition, 2D and 3D object description, and biologically inspired recognition schemes. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI784 | This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. |
Security Concentration [SCCC] |
(12) Credits | |
|---|---|---|
| CSCI784 | This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS667 | This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| IAAS686 | This course analyzes malware analysis tools and techniques in depth. This training has helped forensic investigators, incident responders, security engineers, and IT administrators acquire the practical skills to examine malicious programs that target and infect Windows systems. Understanding the capabilities of malware is critical to an organization’s ability to derive threat intelligence, respond to information security incidents, and fortify defenses. This course builds a strong foundation for reverse-engineering malicious software using a variety of system and network monitoring utilities, a disassembler, a debugger, and other tools useful for turning malware inside-out. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS735 | This course will provide the framework for the techniques and tools used for the extraction of information from digital equipment. Computer forensic tools will be used to gain a thorough understanding of the processes and techniques used in acquiring information and evidence. Topics include federal guidelines for search and seizures, investigating network intrusions, software forensics, and audit logs. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS715 |
Technology Management
Technology Management (TECH MGMT MS)
33 Credits
MASTER OF SCIENCE • 33 CREDITS • TECH MGMT MS
PROGRAM DESCRIPTION
The objective of the Master of Science in Technology Management is to offer a high quality, interdisciplinary technical and business graduate curriculum in technology management for today’s organizations. This program is designed to prepare graduates for a life-long career addressing critical leadership roles in private, public or government organizations. The MS in Technology Management combines a set of business and technical competencies to give Davenport University graduates the competitive advantages needed to lead information technology departments in the global economy.
TECHNOLOGY FOUNDATIONAL REQUIREMENTS
All students admitted into the Davenport University Master of Science in Technology Management are expected to have the necessary undergraduate preparation, as outlined in the Admissions Requirements, prior to entering the 600-level courses. Students who have not successfully completed equivalent undergraduate courses will be required to complete the following graduate (500-level) foundational courses or the undergraduate level equivalent courses. A grade of “B” or better must be earned in each course to show proficiency.
Graduate Level Foundational Courses:
- IAAS581 Information Security and Assurance
- STAT500 Statistics for Business
CURRICULUM
Students will apply leadership tactics, basic observational methods and logical reasoning to demonstrate best practices in problem solving with foundational knowledge in the following areas: industry regulations, network technologies, product and project management, risk mitigation, business continuity, information technology, disaster recovery, total quality management, budgeting and return on investment by using appropriate tools, methods and applications. Students will also choose electives based on their career focus and complete a thesis under the direct guidance of a faculty member.
The elective courses will provide an introduction to the different technical and administrative aspects of Technology Management. Topics will include: wireless networks, accounting information systems, banking and financial security, as well as leadership and change management strategies.
MASTER'S THESIS
A thesis paper forms the Capstone of this Master of Science in Technology Management program. The Capstone is a comprehensive research paper encompassing the learning from the students’ coursework in the program. Prior to enrolling in the CAPS798 Technology Management Thesis course, students must have both an approved Capstone Intent Form and an approved Research Proposal on file with the Program Director.
The final thesis paper is to be completed under the guidance of your faculty advisor and/or university designated faculty member during the CAPS798 course. More details on the master’s thesis and capstone process may be found in the Capstone Guidebook available from your faculty advisor.
NOTE: PMP®, PgMP®, CAPM®, PMI-SP®, PMI-RMP®, and PMI-ACP® are registered marks of the Project Management Institute, Inc.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
24 Credits | |
|---|---|---|
| CISP600 | This course reviews the major content areas of information systems management that will be examined at various organizational levels of MS Technology Management. The major content areas (IT domains) to be covered include information technology management, networking, Web, database, programming and systems development. Upon completion of this course, students will be prepared to analyze, define, and research the unique management considerations of each domain within various organization levels. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| FINC610 | This course applies finance concepts to evaluate and manage budgets in financial decision making in the global environment. The course will include a foundational knowledge of accounting principles such as budget development and execution, program initiation, cost and revenue estimation, budget strategy and evaluation. Students will prepare a plan to obtain funding and manage a project or department budget. Basic financial concepts are covered such as capital budgeting, working capital management, risk and return measurement, cost classification, debt and equity financing and cash flow analysis. Students should be familiar with Microsoft Excel. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| GPMT630 | This course covers the fundamental concepts and applied techniques for cost effective management of both long-term programs and short-term projects. The content deals with planning, scheduling, organizing, and controlling projects using agile methodology for software development. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS600 | This course is a comprehensive study of the techniques used to protect information infrastructure and assets, with a primary focus on the Defense In Depth model that emphasizes the role of people, process and technology. Topics include security problems in computing, networks and distributed systems, and the criticality of the CIA triad; confidentiality, integrity and availability of technology-based resources. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Required undergraduate or 500+ level prerequisite courses | |
| IAAS667 | This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| STAT615 | This course explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. The course will also survey decision making and making recommendations using qualitative and quantitative data. Students will also discover threats to internal and external validity for quantitative research. Minitab will be used throughout the course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Completion of an undergraduate course in introductory statistics (STAT220) course or STAT500 | |
| TMGT685 | Upon completion of this course students will be prepared to incorporate the strategies and processes of different leadership models and organizational change into their personal leadership plan. Students will explore the leader’s role during technological changes and best approaches to lead and manage these changes within the organization. The course will survey how transformational leadership can be applied to foster innovation, technological change, examine the relationships between developing enterprise level, innovative strategies and performing in the role of a transformational CIO leader. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| TMGT788 | This course on statistics explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. Note: This class is preparatory to beginning the Technology Management Thesis and should be completed, at minimum, the semester prior to registration for CAPS798. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): STAT615 |
Elective Courses - Select two (2) of the following: |
6 Credits | |
|---|---|---|
| GPMT699 | This course prepares students for the Project Management Professional (PMP)® certification exam developed and conducted by the Project Management Institute (PMI). This PMI® Authorized PMP® Exam Prep course provides a focused review of subject matter for the current exam and includes PMI-developed course content. Note: Successful completion of this preparatory course does not guarantee passing the exam. In addition, to sit for certification exams, students must meet educational and work experience requirements. Please refer to www.pmi.org for specific exam requirements. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): GPMT287 or equivalent experience. NOTE: PMP®, Project Management Professional (PMP)®, PMBOK® and PMI® are registered marks of the Project Management Institute, Inc. | |
| TMGT655 | This course surveys the technical and managerial challenges of leading innovation in high-tech enterprises and industries. Particular consideration is given to the forces affecting the nature and rate of technological innovation and the managerial alternatives available to both established and entrepreneurial organizations. The course explores sources of innovation, including acquisitions and alliances, real options thinking for investing under uncertainty, managing new ventures and developing effective processes and organizational structures for driving sustainable results. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): CISP600 | |
| TMGT750 | This course explores the thinking processes CIO’s use when solving IT problems, making decisions, formulating IT strategies, and executing IT strategic plan. This course will survey CIO’s best practices and current industry standards. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT655 and TMGT685 |
Capstone |
3 Credits | |
|---|---|---|
| CAPS798 | A thesis project forms the capstone of this Master of Science program. In order to register, a student must complete all course requirements for this degree and submit an acceptable proposal to the technology management faculty for approval via a capstone intent form. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT788, last semester; Technology Core Courses and Management and Leadership Core Courses completed. |
Computer Science
Computer Science (COMP SCIE MS)
30 Credits
MASTER OF SCIENCE • 30 CREDITS • COMP SCIE MS
The Master Program in computer science emphasizes software development, theoretical foundations of computer science and cyber security. It is designed to prepare students for professional positions in industry, government and business, and to provide preparation for graduate work at the doctoral level.
Students without a BS in Computer Science may need to complete the following courses before beginning 600-level courses:
• CSCI531 Introduction to Programming
• CSCI534 Object Oriented Programming with C#
• CSCI545 Data Structures and Algorithms
• MATH515 Calculus I
Which class should I take? When should I take it?
See our Recommended Program Sequences:
- Computer Science, MS - Concentration: Computer Science (web)
- Computer Science, MS - Concentration: Computer Science (pdf)
- Computer Science, MS - Concentration: Security (web)
- Computer Science, MS - Concentration: Security (pdf)
Core Courses |
18 Credits | |
|---|---|---|
| CSCI635 | General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture, bootloader, device drivers and I/O. Advanced topics may include: processes and threads, CPU scheduling; process synchronization; deadlock, threads, memory management; cache; main memory; virtual memory; virtual machine; shared-memory and message-passing based parallelism; clusters; database concepts; security and protection; authentication; and cloud computing. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI655 | The study of the principles, designs, implementations, performance and security issues and areas of current research in computer networks. This may include various types of computer buses, local area networks, long haul networks and layered network models. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI672 | This course covers the theory of computer science emphasizing automata, grammars computation and their applications in the specification of languages and computer systems, models of computation and complexity. Finite-state machines, pushdown automata, Turing machines, regular expressions, decidability, computational complexity, including classes P, NP, NP-complete, NP-hard, and PSPACE will be explored. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI728 | This course will study the design and analysis of algorithms, their correctness, their limitations and their relationship to other algorithms. Students will learn how to analyze a problem and determine its reducibility to a common problem with a current solution. Topics covered may also include Computational Geometry, NP-Completeness, Approximation Algorithms, Dynamic Programming, Greedy Algorithms and Reductions. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. |
Thesis/Project (More details on the Master Research Thesis or Master Project may be found in the Capstone Guidebook available from your faculty advisor) |
(6) Credits | |
|---|---|---|
| CSCI794 or CSCI798 | Master Project or Master Research Thesis | 6 |
Choose one of the following Concentrations: |
12 Credits |
|---|
Computer Science Concentration [CSCC] |
(12) Credits | |
|---|---|---|
| CSCI678 | This course will look at algorithms and concepts that are popular in the artificial intelligence field. Topics covered may include knowledge representation, constraint satisfaction problems, classical search, adversarial search, probabilistic reasoning, reinforcement learning, and robotics. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI744 | This course will look at the algorithms and concepts that are popular in the fields of data mining and machine learning. Topics covered may include deep learning, convolutional neural networks, linear and nonlinear models for classification, kernel methods, support vector machines and dimensionality reduction techniques. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI756 | This course will look at current research progress and trends in the Computer Vision field. Topics covered may include scene analysis, object detection and tracking, segmentation, texture and texture based recognition, 2D and 3D object description, and biologically inspired recognition schemes. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| CSCI784 | This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. |
Security Concentration [SCCC] |
(12) Credits | |
|---|---|---|
| CSCI784 | This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS667 | This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| IAAS686 | This course analyzes malware analysis tools and techniques in depth. This training has helped forensic investigators, incident responders, security engineers, and IT administrators acquire the practical skills to examine malicious programs that target and infect Windows systems. Understanding the capabilities of malware is critical to an organization’s ability to derive threat intelligence, respond to information security incidents, and fortify defenses. This course builds a strong foundation for reverse-engineering malicious software using a variety of system and network monitoring utilities, a disassembler, a debugger, and other tools useful for turning malware inside-out. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS735 | This course will provide the framework for the techniques and tools used for the extraction of information from digital equipment. Computer forensic tools will be used to gain a thorough understanding of the processes and techniques used in acquiring information and evidence. Topics include federal guidelines for search and seizures, investigating network intrusions, software forensics, and audit logs. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS715 |
Master of Science in Health Informatics and Information Management
Master of Science in Health Informatics and Information Management (HIIM MS)
33 Credits
MASTER OF SCIENCE IN HEALTH INFORMATICS AND INFORMATION MANAGEMENT • 33 CREDITS • HIIM MS
Davenport University's graduate program in Health Informatics and Information Management is an interdisciplinary program providing a unique blend of business, technology and health care graduate education for current health system environments. Today's health information management professionals are hybrids who work closely with technology professionals, management professionals and health care providers to ensure the integrity, confidentiality, and appropriate access of health care information. Reflecting the most contemporary practices in the field, the program is structured to provide multiple perspectives in the development, implementation, and maintenance of information and data systems, data analysis, privacy and security, as well as strategic and operational resource policy and planning. This inter-disciplinary program prepares graduates to perform and lead activities related to access, protection, and implementation of systems to analyze and leverage health information into business intelligence for improved decision-making in the information driven, knowledge-based environment. Students may select from the basic Master’s degree at 33 credit hours, or may obtain an additional Data Analytics Certificate by taking two additional courses.
Health Informatics and Information Management Foundational Requirements:
When accepted, a student may be required to complete up to three additional courses if the student’s previous academic experiences do not display they have successfully completed courses focused on Anatomy & Physiology, Pathophysiology, and/or Medical Terminology. These courses can be completed in conjunction with the program’s core courses but must be completed before the student’s final semester.
Students who have not successfully completed equivalent undergraduate courses, outlined in the Admissions Requirements, will be required to complete the following graduate foundational courses or the undergraduate level equivalent courses before taking 600-level courses. A grade of “C” or better must be earned in each foundational course to show proficiency.
Graduate Level Foundational Courses:
CISP547 Database Design
HINT770 Clinical Vocabulary and Health Records (or undergraduate equivalent)
IAAS581 Information Security and Assurance
STAT500 Statistics for Business
The two Data Analytics courses taken as requirements within the Master of Science in Health Informatics and Information Management and they may also be used as part of a Graduate Certificate in Data Analytics or as part of the Master of Science in Data Analytics
Which class should I take? When should I take it?
See our Recommended Program Sequences:
- Health Informatics and Information Management, MS (web)
- Health Informatics and Information Management, MS (pdf)
Courses |
30 Credits | |
|---|---|---|
| DATA610 | Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA667 | Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HCMG630 | This course provides a systematic overview of the U.S. Healthcare Delivery System. Students will examine key components involved in the delivery and provision of healthcare services, including cultural diversity. This course also provides students an opportunity to examine the origin, development, structure, organization, and operational issues as they relate to hospitals and healthcare delivery systems. Note: A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HCMG750 | The focus of this course is to provide a working knowledge of payment policies and reimbursement methodologies used in health care and how they vary by payment source (governmental, private, and capitated insurance). Methodologies used by facilities and practitioners will be applied and compared. Factors affecting payment will be discussed. Costing methodologies, revenue cycle management, purchasing strategies, budgeting, and variance analysis applied to health care are examined. Note: A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): HCMG630 | |
| HINT601 | This seminar is required in the first semester of acceptance to the College of Health Professions Health Informatics and Information Management program. The program expectations and the HIIM Student Handbook will be reviewed. Students in this course must register and complete the required Criminal Background Check (CBC) and Drug Screen (DS). Note: This course is graded on a Pass/Fail basis. If the CBC/DS portion of the class is not completed in the specified time frame, a failing grade will be given for the course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HINT730 | This course will provide an overview of the legal processes and compliance issues related to health data. Students will review HIPAA compliance requirements as well as review risk management strategies and policies. Students will develop a training program related to legal issues and compliance and incorporate project management methodologies. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| HINT760 | This course provides an introduction to research study design, methods, descriptive and inferential statistics needed to conduct research studies in the health information management domains. Topics include institutional review boards, ethics in research, the research process, data collection and presentation of data. Students will establish the framework for their capstone thesis/project. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| HINT775 | Students in this course will explore the concepts of information governance. Data management policies will be evaluated to ensure they are compliant with federal and state regulations. The course will discuss managing information while supporting the organization’s strategy, operations and risk requirements. Students will review and evaluate the processes needed in today's e-health environment related to information interoperability. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS600 | This course is a comprehensive study of the techniques used to protect information infrastructure and assets, with a primary focus on the Defense In Depth model that emphasizes the role of people, process and technology. Topics include security problems in computing, networks and distributed systems, and the criticality of the CIA triad; confidentiality, integrity and availability of technology-based resources. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Required undergraduate or 500+ level prerequisite courses | |
| IAAS675 | This course will provide the framework for developing and integrating security, critical infrastructures and assets prevalent in the healthcare and hospital industries. Legislation, policies, and case studies specific to the healthcare services field will be highlighted. Topics will include risks and vulnerabilities, security safeguards and standards, access control, audits, disaster recovery planning, security policy and procedures, and physical and logical security systems. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| MGMT653 | This course is designed to provide new ways of thinking about leadership philosophies and strategies to influence the behaviors of individuals and groups in organizations. Students begin with an exploration of the nature of effective leadership and leadership theories. Understanding power, creating change, developing teams, and guiding group decisions are examined in the context of the roles of a leader. Students learn how to recognize leadership traits and approaches so they can develop their own leadership style. Case studies involving real-world situations that confront leaders are used so that students can formulate strategies to improve the performance of followers through effective leadership. A grade of C or better is required on the final assessment in order to earn a passing grade in this course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): BUSN520 |
Capstone |
3 Credits | |
|---|---|---|
| HINT799 | A thesis or project is required for the capstone in the HIIM program. In order to register, a student must have completed all course requirements for this degree and submit an acceptable proposal to the HIIM Program Director. The thesis consists of original research on any topic in the area of health information management, health information systems and/or health informatics. Oral presentation and defense of the thesis is required. The capstone project will be a rigorous project focused on a real-world health information, health information systems or health informatics setting and application of problem-solving methods for development of solutions. A final written report is required. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): All HIIM MS courses; Program Director Approval; must be taken in last semester. |
Master of Science in Data Analytics
Master of Science in Data Analytics (DATANLYTC MS)
30 Credits
MASTER OF SCIENCE IN DATA ANALYTICS • 30 CREDITS • DATANLYTC MS
Data Analytics is used to analyze vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. All aspects of the business and medical communities, as well as government agencies and non-profit organizations, rely on data analytics, yet are hampered by a growing shortage of data analysts. Davenport’s 30 credit hour Master of Science in Data Analytics responds to this need. The degree is delivered jointly by the College of Arts and Sciences in partnership with the Colleges of Technology, Business and Health Professions. The program is online and prepares individuals to conduct sophisticated analysis of existing data and create new data systems and methodologies. It is also designed to enable these individuals to make recommendations that increase effective use of data to help organizations meet specific goals and respond to new opportunities. The program uses industry standard software in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Course progression and content is carefully formulated to build competency in data analysis for students from a broad range of disciplines and experiences, including those who are new to the field.
DATA courses are only offered in a 15-week online format.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
12 Credits | |
|---|---|---|
| DATA610 | Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA625 | This course introduces students to data mining methods and applications. It covers basic concepts and tools for data mining, including data sources, data cleaning tools and methods, mainstream algorithms for data mining, statistical modeling, popular tools for mining structured data and unstructured data. Students will also learn how data mining can be effectively used in various application areas to drive decisions and actions. Students get hands-on practice by conducting a data analytics project using real world data sets. | |
| DATA667 | Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA710 | R programming language concepts are covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples. Upon completing this course, students will be able to employ advanced modeling techniques to write R code to conduct data analysis with strong reusability. |
Advanced Courses |
15 Credits | |
|---|---|---|
| DATA728 | This course will be a more advanced treatment of data mining and predictive analytics concepts introduced in DATA625 with a focus on customer relationship management (CRM). Using customized variations of the industry-standard CRISP-DM methodology, it will provide an experiential learning opportunity to explore all six phases of the model. This includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Industry standard tools and techniques are utilized to prepare students with the knowledge to be successful in current organizations. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA625 | |
| DATA742 | Students will be introduced to the concept of the data warehouse and the role it plays in an organization’s overall business intelligence and analytics strategy. This course will cover the two predominate warehouse design strategies, as well as hybrid designs that combine best practices from both areas, including the requirements of a data warehouse, selecting the proper design strategy, choosing the proper tools to support that design, selecting metrics for monitoring performance, data quality, and planning future enhancements. Students will be able to build a high-level plan for implementing a data warehouse in their organization or planning future changes to an existing warehouse if present. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA758 or DATA790 | Essentials of Cloud Computing or Data Analytics Internship | 3 |
| DATA772 | This course covers statistical procedures used in data analytics with emphasis on hands-on practice. Industry standard software is used to import and prepare data for model development as well as for developing various types of regression models. Assessment of model performance and methods for model selection are also covered. Emphasis is also placed on parameter estimation, variable selection, and diagnostic checking of these models and their use for statistical inference and prediction. Both numerical and graphical techniques are used for diagnostics and reporting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA710 | |
| DATA785 | This course covers statistical modeling in the use of statistical methods to develop models that can be used for predicting future numerical or categorical outcomes in processes for disciplines ranging from business to science. The philosophy of modeling as well as common modeling methods and model adequacy assessment procedures are covered. Industry standard software is used to prepare data, develop and assess models, obtain predictions, and present results. The main thrust of the course is on the application of predictive modeling rather than the theory behind it. Selected projects will be used to provide hands-on experience with the various steps involved in modeling and predicting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA772 |
Capstone Project |
3 Credits | |
|---|---|---|
| DATA792 | Students will apply all of their theoretical and practical experience to design and execute an analytics project on a chosen topic as a culmination of their analytics program, thereby demonstrating competency of program learning outcomes. Students will select the techniques to be used in the study, collect and analyze data for the purpose of drawing conclusions and making recommendations to the decision makers of an organization. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Course may only be elected in the final semester of the program. |
Master of Science in Data Analytics
Master of Science in Data Analytics (DATANLYTC MS)
30 Credits
MASTER OF SCIENCE IN DATA ANALYTICS • 30 CREDITS • DATANLYTC MS
Data Analytics is used to analyze vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. All aspects of the business and medical communities, as well as government agencies and non-profit organizations, rely on data analytics, yet are hampered by a growing shortage of data analysts. Davenport’s 30 credit hour Master of Science in Data Analytics responds to this need. The degree is delivered jointly by the College of Arts and Sciences in partnership with the Colleges of Technology, Business and Health Professions. The program is online and prepares individuals to conduct sophisticated analysis of existing data and create new data systems and methodologies. It is also designed to enable these individuals to make recommendations that increase effective use of data to help organizations meet specific goals and respond to new opportunities. The program uses industry standard software in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Course progression and content is carefully formulated to build competency in data analysis for students from a broad range of disciplines and experiences, including those who are new to the field.
DATA courses are only offered in a 15-week online format.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
12 Credits | |
|---|---|---|
| DATA610 | Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA625 | This course introduces students to data mining methods and applications. It covers basic concepts and tools for data mining, including data sources, data cleaning tools and methods, mainstream algorithms for data mining, statistical modeling, popular tools for mining structured data and unstructured data. Students will also learn how data mining can be effectively used in various application areas to drive decisions and actions. Students get hands-on practice by conducting a data analytics project using real world data sets. | |
| DATA667 | Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA710 | R programming language concepts are covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples. Upon completing this course, students will be able to employ advanced modeling techniques to write R code to conduct data analysis with strong reusability. |
Advanced Courses |
15 Credits | |
|---|---|---|
| DATA728 | This course will be a more advanced treatment of data mining and predictive analytics concepts introduced in DATA625 with a focus on customer relationship management (CRM). Using customized variations of the industry-standard CRISP-DM methodology, it will provide an experiential learning opportunity to explore all six phases of the model. This includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Industry standard tools and techniques are utilized to prepare students with the knowledge to be successful in current organizations. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA625 | |
| DATA742 | Students will be introduced to the concept of the data warehouse and the role it plays in an organization’s overall business intelligence and analytics strategy. This course will cover the two predominate warehouse design strategies, as well as hybrid designs that combine best practices from both areas, including the requirements of a data warehouse, selecting the proper design strategy, choosing the proper tools to support that design, selecting metrics for monitoring performance, data quality, and planning future enhancements. Students will be able to build a high-level plan for implementing a data warehouse in their organization or planning future changes to an existing warehouse if present. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| DATA758 or DATA790 | Essentials of Cloud Computing or Data Analytics Internship | 3 |
| DATA772 | This course covers statistical procedures used in data analytics with emphasis on hands-on practice. Industry standard software is used to import and prepare data for model development as well as for developing various types of regression models. Assessment of model performance and methods for model selection are also covered. Emphasis is also placed on parameter estimation, variable selection, and diagnostic checking of these models and their use for statistical inference and prediction. Both numerical and graphical techniques are used for diagnostics and reporting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA710 | |
| DATA785 | This course covers statistical modeling in the use of statistical methods to develop models that can be used for predicting future numerical or categorical outcomes in processes for disciplines ranging from business to science. The philosophy of modeling as well as common modeling methods and model adequacy assessment procedures are covered. Industry standard software is used to prepare data, develop and assess models, obtain predictions, and present results. The main thrust of the course is on the application of predictive modeling rather than the theory behind it. Selected projects will be used to provide hands-on experience with the various steps involved in modeling and predicting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA772 |
Capstone Project |
3 Credits | |
|---|---|---|
| DATA792 | Students will apply all of their theoretical and practical experience to design and execute an analytics project on a chosen topic as a culmination of their analytics program, thereby demonstrating competency of program learning outcomes. Students will select the techniques to be used in the study, collect and analyze data for the purpose of drawing conclusions and making recommendations to the decision makers of an organization. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Course may only be elected in the final semester of the program. |
Master of Science in Technology Management
Master of Science in Technology Management (TECH MGMT MS)
33 Credits
MASTER OF SCIENCE IN TECHNOLOGY MANAGEMENT • 33 CREDITS • TECH MGMT MS
PROGRAM DESCRIPTION
The objective of the Master of Science in Technology Management is to offer a high quality, interdisciplinary technical and business graduate curriculum in technology management for today’s organizations. This program is designed to prepare graduates for a life-long career addressing critical leadership roles in private, public or government organizations. The MS in Technology Management combines a set of business and technical competencies to give Davenport University graduates the competitive advantages needed to lead information technology departments in the global economy.
TECHNOLOGY FOUNDATIONAL REQUIREMENTS
All students admitted into the Davenport University Master of Science in Technology Management are expected to have the necessary undergraduate preparation, as outlined in the Admissions Requirements, prior to entering the 600-level courses. Students who have not successfully completed equivalent undergraduate courses will be required to complete the following graduate (500-level) foundational courses or the undergraduate level equivalent courses. A grade of “B” or better must be earned in each course to show proficiency.
Graduate Level Foundational Courses:
IAAS581 Information Security and Assurance
STAT500 Statistics for Business
CURRICULUM
Students will apply leadership tactics, basic observational methods and logical reasoning to demonstrate best practices in problem solving with foundational knowledge in the following areas: industry regulations, network technologies, product and project management, risk mitigation, business continuity, information technology, disaster recovery, total quality management, budgeting and return on investment by using appropriate tools, methods and applications. Students will also choose electives based on their career focus and complete a thesis under the direct guidance of a faculty member.
The elective courses will provide an introduction to the different technical and administrative aspects of Technology Management. Topics will include: wireless networks, accounting information systems, banking and financial security, as well as leadership and change management strategies.
MASTER'S THESIS
A thesis paper forms the Capstone of this Master of Science in Technology Management program. The Capstone is a comprehensive research paper encompassing the learning from the students’ coursework in the program. Prior to enrolling in the CAPS798 Technology Management Thesis course, students must have both an approved Capstone Intent Form and an approved Research Proposal on file with the Program Director.
The final thesis paper is to be completed under the guidance of your faculty advisor and/or university designated faculty member during the CAPS798 course. More details on the master’s thesis and capstone process may be found in the Capstone Guidebook available from your faculty advisor.
NOTE: PMP®, PgMP®, CAPM®, PMI-SP®, PMI-RMP®, and PMI-ACP® are registered marks of the Project Management Institute, Inc.
Which class should I take? When should I take it?
See our Recommended Program Sequences:
Core Courses |
24 Credits | |
|---|---|---|
| CISP600 | This course reviews the major content areas of information systems management that will be examined at various organizational levels of MS Technology Management. The major content areas (IT domains) to be covered include information technology management, networking, Web, database, programming and systems development. Upon completion of this course, students will be prepared to analyze, define, and research the unique management considerations of each domain within various organization levels. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| FINC610 | This course applies finance concepts to evaluate and manage budgets in financial decision making in the global environment. The course will include a foundational knowledge of accounting principles such as budget development and execution, program initiation, cost and revenue estimation, budget strategy and evaluation. Students will prepare a plan to obtain funding and manage a project or department budget. Basic financial concepts are covered such as capital budgeting, working capital management, risk and return measurement, cost classification, debt and equity financing and cash flow analysis. Students should be familiar with Microsoft Excel. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| GPMT630 | This course covers the fundamental concepts and applied techniques for cost effective management of both long-term programs and short-term projects. The content deals with planning, scheduling, organizing, and controlling projects using agile methodology for software development. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| IAAS600 | This course is a comprehensive study of the techniques used to protect information infrastructure and assets, with a primary focus on the Defense In Depth model that emphasizes the role of people, process and technology. Topics include security problems in computing, networks and distributed systems, and the criticality of the CIA triad; confidentiality, integrity and availability of technology-based resources. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Required undergraduate or 500+ level prerequisite courses | |
| IAAS667 | This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): IAAS600 | |
| STAT615 | This course explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. The course will also survey decision making and making recommendations using qualitative and quantitative data. Students will also discover threats to internal and external validity for quantitative research. Minitab will be used throughout the course. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Completion of an undergraduate course in introductory statistics (STAT220) course or STAT500 | |
| TMGT685 | Upon completion of this course students will be prepared to incorporate the strategies and processes of different leadership models and organizational change into their personal leadership plan. Students will explore the leader’s role during technological changes and best approaches to lead and manage these changes within the organization. The course will survey how transformational leadership can be applied to foster innovation, technological change, examine the relationships between developing enterprise level, innovative strategies and performing in the role of a transformational CIO leader. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. | |
| TMGT788 | This course on statistics explores applications for the practitioner in industry. Included are data descriptions, measures of central tendency and variability, probability, tests of hypotheses, regression analysis and analysis of categorical data. Selection of research problems, analysis of literature, individual investigations, preparing reports, and proposal writing are detailed. Note: This class is preparatory to beginning the Technology Management Thesis and should be completed, at minimum, the semester prior to registration for CAPS798. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): STAT615 |
Elective Courses - Select two (2) of the following: |
6 Credits | |
|---|---|---|
| GPMT699 | This course prepares students for the Project Management Professional (PMP)® certification exam developed and conducted by the Project Management Institute (PMI). This PMI® Authorized PMP® Exam Prep course provides a focused review of subject matter for the current exam and includes PMI-developed course content. Note: Successful completion of this preparatory course does not guarantee passing the exam. In addition, to sit for certification exams, students must meet educational and work experience requirements. Please refer to www.pmi.org for specific exam requirements. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): GPMT287 or equivalent experience. NOTE: PMP®, Project Management Professional (PMP)®, PMBOK® and PMI® are registered marks of the Project Management Institute, Inc. | |
| TMGT655 | This course surveys the technical and managerial challenges of leading innovation in high-tech enterprises and industries. Particular consideration is given to the forces affecting the nature and rate of technological innovation and the managerial alternatives available to both established and entrepreneurial organizations. The course explores sources of innovation, including acquisitions and alliances, real options thinking for investing under uncertainty, managing new ventures and developing effective processes and organizational structures for driving sustainable results. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): CISP600 | |
| TMGT750 | This course explores the thinking processes CIO’s use when solving IT problems, making decisions, formulating IT strategies, and executing IT strategic plan. This course will survey CIO’s best practices and current industry standards. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT655 and TMGT685 |
Capstone |
3 Credits | |
|---|---|---|
| CAPS798 | A thesis project forms the capstone of this Master of Science program. In order to register, a student must complete all course requirements for this degree and submit an acceptable proposal to the technology management faculty for approval via a capstone intent form. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): TMGT788, last semester; Technology Core Courses and Management and Leadership Core Courses completed. |