Data Analytics Certificate
Data analytics uses a variety of techniques to examine large amounts of data to discover patterns that can lead to business insights. Data analytics has broad applicability in customer behavior analysis, fraud detection, scientific inquiry, process improvement, financial analysis, trend analysis, forecasting, and decision-making. Techniques may include statistical methods, data mining, modeling and simulation, and data visualization. The certificate is designed to equip students to apply the theory and practice of data analytics to solving problems in a variety of economic, social, and scientific domains.
Program Related Information
Program Contact
Emily Wiemers, Graduate Advisor
402.554.3819
ewiemers@unomaha.edu
Prospective Student Admission: advising-cist@unomaha.edu
Program Website
Admissions
General Application Requirements and Admission Criteria
Application Deadlines
- Spring 2027: December 1
- Summer 2027: April 1
- Fall 2027: July 1
Other Requirements
- The minimum undergraduate grade point average requirement for the data analytics certificate program is 3.0 or equivalent score on a 4.0 scale. Applicants should have the equivalent of a four-year undergraduate degree.
-
English Language Proficiency: Applicants are required to have a command of oral and written English. Those who do not hold a baccalaureate or other advanced degree from the United States, OR a baccalaureate or other advanced degree from a predetermined country on the waiver list, must meet the minimum language proficiency score requirement in order to be considered for admission.
- Internet-based TOEFL: 80, IELTS: 6.5, PTE: 53, Duolingo: 110
- Resume: Submit a detailed resume indicating your work experience and background.
- OPTIONAL Statement of Purpose: Applicants may submit a statement of purpose with a maximum of 750 words that address:
- why you want to study at UNO
- career goals
- relevant qualifications or work experience that demonstrate potential for success in the graduate program
- motivations for pursuing graduate education
Degree Requirements
Foundation Requirements
All students admitted to the data analytics certificate must demonstrate prerequisite knowledge in areas such as programming and relational databases before beginning graduate coursework. This requirement is met through a set of zero-credit, online, asynchronous Readiness Modules. The modules provide essential foundational skills that support success in the program.
Students may satisfy individual module requirements through prior coursework or by passing a test-out assessment. Students who do not test out must complete the corresponding modules by the end of the first week of classes.
Readiness Modules do not carry academic credit and cannot be applied toward the 12 credit hours required for the degree.
Requirements
No more than two courses (6 credit hours maximum) can be used on two MIS-related certificates (data analytics, information security management, project management, and systems analysis and design).
| Code | Title | Credits |
|---|---|---|
| Core Courses | ||
| Data Engineering | 3 | |
| BUSINESS INTELLIGENCE | ||
| INFORMATION AND DATA QUALITY MANAGEMENT | ||
| NOSQL AND BIG DATA TECHNOLOGIES | ||
| INTERNET OF THINGS (IOT), BIG DATA AND THE CLOUD | ||
| DATA WAREHOUSING AND DATA MINING | ||
| Data Analytics | 3 | |
| ADVANCED STATISTICAL METHODS FOR IS&T | ||
| APPLIED REGRESSION ANALYSIS | ||
| DATA MINING: THEORY AND PRACTICE | ||
| APPLIED STATISTICAL MACHINE LEARNING | ||
| DECISION SUPPORT SYSTEMS | ||
| APPLIED DISTRIBUTION FREE STATISTICS | ||
| APPLIED EXPERIMENTAL DESIGN AND ANALYSIS | ||
| APPLIED MULTIVARIATE ANALYSIS | ||
| GRAPH THEORY & APPLICATIONS | ||
| DETERMINISTIC OPERATIONS RESEARCH MODELS | ||
| MACHINE LEARNING FOR TEXT | ||
| BUSINESS FORECASTING | ||
| Data Visualization | 3 | |
| STORYTELLING WITH DATA | ||
| HUMAN COMPUTER INTERACTION | ||
| Electives | 3 | |
Pick one of the remaining courses from any of the three categories above 1 | ||
| Total Credits | 12 | |