Data Science, MS

The vision of the Master of Science in data science program is to provide flexible, innovative, and technologically current education to rising data professionals who want to prepare for corporate leadership positions through their functional expertise. The interdisciplinary data science program brings together thought leaders in the fields of business, information technology, mathematics, and other units at UNO, including international university partners and local businesses.

This interdisciplinary graduate program is designed to be completed in 24 months. The curriculum includes course modules on topics that address the following major themes: data organization, manipulation, cleaning, and visualization; data analytics; working with massive amounts of data; dealing with missing and messy data; understanding the value of data and creating data products.

Program Related Information

Program Contact

Md Mahbubul Majumder, PhD, Graduate Program Chair (GPC)
402.554.2734
mmajumder@unomaha.edu

Program Website

Admissions

General Application Requirements and Admission Criteria

Application Deadlines

  • Spring 2026:  December 15
  • Fall 2026:  July 1

Other Requirements

  • Minimum GPA of at least 3.0 in 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 U.S., OR a baccalaureate or advanced degree from a pre-determined 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:  An up-to-date resume with details about all relevant IT experience and skills.
  • Optional: One letter of recommendation from a reference who can evaluate your work and/or academic achievements.
  • Interview:  A personal, telephone or Zoom/Microsoft Teams interview is encouraged, but is optional.

Degree Requirements

Foundation Courses

Students must have completed basic courses in the following areas, either as an undergraduate student or prior to enrolling in the first data science course.

  • Introduction to programming: one semester of Java, Python, C++, or other approved programming course
  • Statistics: one semester of undergraduate statistics

Foundation courses do not count towards the plan of study/degree requirements.

Requirements

Core Courses18
STAT 8416
INTRODUCTION TO DATA SCIENCE
STAT 8426
EXPLORATORY DATA VISUALIZATION AND QUANTIFICATION
ECON 8320
TOOLS FOR DATA ANALYSIS
ECON 8310
BUSINESS FORECASTING
or BSAD 8080
 BUSINESS FORECASTING
ISQA 8206
INFORMATION AND DATA QUALITY MANAGEMENT
HCC 8300
RESEARCH FOUNDATIONS
or ISQA 8060
 RESEARCH IN MIS
Concentration12
Select one of the five concentration areas.
Exit Requirement (Capstone, Project or Thesis)6
Specific exit requirements for each concentration are included on the Concentrations tab.
Total Credits36

Exit Requirements

  • Capstone Option: Complete DSCI 8950 OR STAT 8950 and 3 hours of additional electives.
  • Project Option: Complete STAT 8960 and 3 hours of additional electives. 
  • Thesis 6 Credits
    • All candidates should carefully review the Graduate College requirements for forming a supervisory committee, Thesis/Thesis Equivalent Proposal Approval forms and final approval and submission of a thesis.

Concentrations

Business Concentration

Select 12 hours from the following:12
ACCT 8080
CURRENT TECHNOLOGY USE IN ACCOUNTING
BSAD 8376
SUPPLY CHAIN ANALYTICS
BSAD 8066
HEALTHCARE ANALYTICS FOR BUSINESS
BSAD 8396
MARKETING ANALYTICS
BSAD 8426
BUSINESS DEMOGRAPHICS
BSAD 8910
SPECIAL TOPICS IN BUSINESS
ECON 8300
ECONOMETRICS
ECON 8306
QUANTITATIVE APPLICATIONS IN ECONOMICS AND BUSINESS
ECON 8316
BUSINESS INTELLIGENCE AND REPORTING
ECON 8330
DATA ANALYSIS FROM SCRATCH
ECON 8910
SPECIAL STUDIES IN ECONOMICS (Sports Economics)
Total Credits12

Exit Requirement

  • Capstone Option - Complete ECON 8330 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
  • Project Option - Complete STAT 8960 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
  • Thesis Option - All candidates should carefully review the Graduate College requirements for forming a supervisory committee, thesis/thesis equivalent proposal approval forms and final approval and submission of a thesis. The chair of the supervisory committee must be from the College of Business Administration.

Data Science for Health Sciences Concentration

BMI 8100INTRODUCTION TO BIOMEDICAL INFORMATICS3
Select 9 hours from the following:9
BMI 8020
ADVANCED COURSE IN BIOINFORMATICS
BMI 8866
BIOINFORMATICS ALGORITHMS
BMI 8896
COMPUTERIZED GENETIC SEQUENCE ANALYSIS
CSCI 8156
GRAPH THEORY & APPLICATIONS
STAT 8456
INTRODUCTION TO MACHINE LEARNING AND DATA MINING
Total Credits12

Exit Requirement

  • Capstone Option - Complete DSCI 8950 or STAT 8950 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
  • Project Option - Complete STAT 8960 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
     
  • Thesis Option - All candidates should carefully review the Graduate College requirements for forming a supervisory committee, Thesis/Thesis Equivalent Proposal Approval forms and final approval and submission of a thesis. The chair of the supervisory committee must be from the Department of Mathematical and Statistical Sciences.

Information Technology Concentration

Select 12 hours from the following:12
ISQA 8016
BUSINESS INTELLIGENCE
ISQA 8086
SPECIAL TOPICS: INFORMATION SYSTEMS & QUANTITATIVE ANALYSIS
ISQA 8156
ADVANCED STATISTICAL METHODS FOR IS&T
ISQA 8160
APPLIED DISTRIBUTION FREE STATISTICS
ISQA 8340
APPLIED REGRESSION ANALYSIS
ISQA 8410
DATA MANAGEMENT
ISQA 8450
NOSQL AND BIG DATA TECHNOLOGIES
ISQA 8460
INTERNET OF THINGS (IOT), BIG DATA AND THE CLOUD
ISQA 8600
FROM DATA TO DECISIONS
ISQA 8700
DATA MINING: THEORY AND PRACTICE
or CSCI 8350
 DATA WAREHOUSING AND DATA MINING
ISQA 8720
APPLIED STATISTICAL MACHINE LEARNING
ISQA 8736
DECISION SUPPORT SYSTEMS
ISQA 8750
STORYTELLING WITH DATA
ISQA 8810
INFORMATION TECHNOLOGY PROJECT FUNDAMENTALS
ISQA 8910
INFORMATION SYSTEMS INTERNSHIP
ISQA 9120
APPLIED EXPERIMENTAL DESIGN AND ANALYSIS
ISQA 9130
APPLIED MULTIVARIATE ANALYSIS
CSCI 8476
PATTERN RECOGNITION
CSCI 8856
DATABASE MANAGEMENT SYSTEMS
CYBR 8396
MOBILE DEVICE FORENSICS
CYBR 8490
CYBER INVESTIGATIONS
Total Credits12

Exit Requirement

  • Capstone Option - Complete DSCI 8950 or STAT 8950 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
  • Project Option - Complete CSCI 8910 or STAT 8960 and 3 additional hours from any concentration area or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910  (Structure Equation/Hierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling)
  • Thesis Option - All candidates should carefully review the Graduate College requirements for forming a supervisory committee, Thesis/Thesis Equivalent Proposal Approval forms and final approval and submission of a thesis. The chair of the supervisory committee must be from the College of Information Science & Technology.

Interdisciplinary Concentration

Select 12 hours from any of the other concentrations, courses must be approved by your advisor.12
Total Credits12

Exit Requirement

Statistical and Decision Sciences Concentration

Select 12 hours from the following:12
STAT 8446
TIME SERIES ANALYSIS
STAT 8436
LINEAR MODELS
STAT 8456
INTRODUCTION TO MACHINE LEARNING AND DATA MINING
STAT 8700
BAYESIAN STATISTICS
STAT 8730
ADVANCED STATISTICAL MACHINE LEARNING
STAT 8710
DESIGN AND ANALYSIS OF EXPERIMENTS
MATH/CSCI 8306
DETERMINISTIC OPERATIONS RESEARCH MODELS
MATH/CSCI 8316
PROBABILISTIC OPERATIONS RESEARCH MODELS
MATH 8326
COMPUTATIONAL OPERATIONS RESEARCH
MATH 8430
LINEAR PROGRAMMING
MATH/CSCI 8520
ADVANCED TOPICS IN OPERATIONS RESEARCH
MATH 8650
INTRODUCTION TO PROBABILITY MODELS
MATH 8670
TOPICS IN PROBABILITY AND STATISTICS
MATH 8440
NETWORK PROGRAMMING
MATH 8460
INTEGER PROGRAMMING
Total Credits12

Exit Requirement

  • Capstone Option- Complete DSCI 8950 or STAT 8950
  • Project Option - Complete STAT 8960 and 3 additional hours from any of the concentration areas or PSYC 9020, PSYC 9090, PSYC 9100, PSYC 9120, PSYC 9910 (Structure Equation/H ierarchical Linear Modeling), PSYC 9920 (Multilevel Modeling) 
  • Thesis Option - All candidates should carefully review the Graduate College requirements for forming a supervisory committee, Thesis/Thesis Equivalent Proposal Approval forms and final approval and submission of a thesis. The chair of the supervisory committee must be from the Department of Mathematical and Statistical Sciences.