30 TOTAL CREDITS REQUIRED
In this 30-credit-hour program, you’ll complete 15 credit hours of data science online courses before finishing the program with 12 credit hours in an area(s) of your choosing, including four focus areas:
- Social Science
- Business Analytics
- Financial Crime
You can also design your own specialization and put the data to work in the field of your choice.
Then, choose between a three-credit capstone or thesis project to demonstrate your new expertise in a hands-on practicum or research project. The program is designed to be completed in as few as five continuous semesters of study, or about two years.
The curriculum course abstracts on this page are meant to provide a high-level course overview and subject to change based on term, faculty, and/or institutional requirements. View the official data science online course descriptions as written in the Utica University Academic Catalog and in adherence to regional compliance. Select the appropriate Graduate Catalog from the dropdown.
Introduction to Data Science introduces students to important data science goals and objectives that inform data collection and analysis techniques. Students will also embark on developing an understanding of how appropriate quantitative and qualitative methods, data collection techniques, and software help data scientists interpret and apply research findings to help solve real world problems using private and proprietary data sources, as well as publicly available ones. Finally, this course helps students develop advanced critical thinking of research ethics and social responsibilities, as they relate to management and decision sciences.
In Statistical Methods, students learn advanced statistical models for data analysis. This course enables the theoretical understanding and practical application of the principles and techniques of statistical data analysis.
Data Mining introduces students to theoretical concepts and methods in the field of data mining. Students explore data mining methods used for prediction and knowledge discovery in databases (KDD) by using programming software to analyze real-world data.
In Machine Learning, students learn the key machine learning algorithms and their applications to real-world problems. Students learn theoretical foundations and empirical applications of machine learning with hands-on programming assignments and projects.
In Data Visualization, students become effective data storytellers by creating rich visuals to represent and communicate data analysis.
DSC 680 Capstone
The research practicum involves data science research or applied problem solving using data analytics. The experience provides students with the opportunity to analyze data, consider ethical and social implications of the analysis, and draw empirically grounded conclusions.
Prerequisite(s); if any: DSC 611 Co-requisite(s): DSC 611
DSC 690 Thesis
The thesis project is a research project that involves the student conducting the full research process, from selecting a topic, preparing a literature review, to collecting and analyzing data, and completing a discussion and conclusion. Students who are interested in completing a Ph.D. program may be best served by enrolling in this course.
Prerequisite(s); if any: DSC 611 Co-requisite(s): DSC 611
SOCIAL SCIENCE ANALYTICS SPECIALIZATION
Study human population size, growth, density, and change while focusing on fertility, mortality, and migration patterns in the United States. You’ll gain a comparative perspective to allow for the analysis of various demographic variables.
Learn how behavioral economics questions the underlying assumptions of classical economics, and how it incorporates social sciences theories to better understand and predict how people make decisions. You’ll explore how these insights — combined with data collected from experiments — can be used to develop strategies to address individual and societal problems.
Prerequisites: DSC 501, DSC 503, DSC 607, DSC 609, or Permission of Instructor
CYB 605 Principles of Cybersecurity
Foundational concepts and processes for information security in cyberspace: incident response, reporting, containment, and restoration of the information infrastructure.
CYB 606 Cyberspace and Cybersecurity
Introduction to the disciplines of cyberspace and cybersecurity including key concepts, terms and definitions. Examination of threats, vulnerabilities and countermeasures associated with cybersecurity. Introduce the topics of cybersecurity policy, risk and compliance.
Explore foundational concepts and processes in the sub-discipline of cyber intelligence.
Develop a broad understanding of the concepts and processes of counterintelligence in cyberspace. Explore topics including counterintelligence missions, defensive and offensive counterintelligence, and counterespionage.
Learn about open-source cyber surveillance including the responsible, legal, and ethical use of data and information gathered from the use of unmanned, semi-autonomous systems, Web data mining, social networks, and other modern cyber systems.
Explore data collection, fusion, integration, and analysis problems selected from the following advanced surveillance technologies: acoustic, electromagnetic, sensors, special (magnetic, cryptologic, computer), and human networks.
BUSINESS ANALYTICS SPECIALIZATION
Explore economic forces and how they relate to a firm’s profitability and growth, as well as economic thinking. You’ll take a close look at principles of microeconomics and how they apply to managerial decision-making.
Explore corporate financial analysis, working capital management, and capital budgeting issues while learning to use financial models and tools that inform leaders about the long-term viability of a business and to discover financial fraud.
Investigate the various functions and ethical impacts of management within an organization. You’ll examine strategy, research and development, marketing, operations, and the supply chain.
Part I of a course that helps prospective leaders understand how to apply accounting and finance concepts. You’ll also explore how to interpret and apply financial data to inform decision-making.
This course is the companion to BUS 622.View Course Abstract
Gain an in-depth understanding of how to apply accounting and finance concepts. Learn how the interpretation and application of financial data can affect decision-making. Part II of a course for prospective leaders.
Prerequisite: BUS 621View Course Abstract
FINANCIAL CRIME SPECIALIZATION
Study the foundations of financial crime and compliance management. Focus on thematic areas: Management, economic crime, technology, analytics, and research skills.
You’ll study financial crime in the context of business operations, methods of detection, and methods of investigation including the analysis of financial documents, investigative process and techniques, and preparation of investigative case reports.
This course is designed to familiarize students with innovative analytic approaches used to perform complex fraud analysis. Topics include: link analysis, data mining, advanced statistical tools, case management systems, and expert system approaches such as neural network early-warning software.
In Part I of this course, learn how to shape executive decision-making by ensuring the data used to inform decisions is correct.
This is the prerequisite course to BUS 632.View Course Abstract
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