STEM-Certified Program
Concentrations are available in:
The Master of Science in Data Analytics program provides students with the critical skills necessary
to become a
Data Analyst or Data Scientist working in a variety of fields across all industries. The integration
of Data Analytics
and Informatics has created a demand for professionals who can make data-driven decisions that
propel their organizations forward.
This online/real-time and/or in-class M.S. in Data Analytics program prepares graduate students to
make sense of
real-world situations, conditions, and frequent everyday activities by synthesizing and mining big
data with the
intention of uncovering patterns, relationships, and trends. Big data has emerged as the driving
force behind critical business decisions. Advances in our ability to collect, store, and process
different kinds of data from
traditionally unconnected sources enable us to answer complex, data-driven questions in ways that
have never
been possible before.
Data analytics combines information management, statistics, analytical thinking, quantitative
methods, data
modeling, data warehousing, and data mining to produce visualizations and other business
intelligence models
that help organizational leaders predict and evaluate best practices.
Data Analytics Program Requirements
3
Core courses for both concentrations.
-
MDAN 623
Statistics for Data Analytics
- This course introduces univariate data analysis methods using statistics. Data visualization
methods and practices, and an overview of sampling techniques for data collection. Specifically,
this course teaches introductory statistical methods for the analysis and visualization of data
and basic concepts of probability theory. Course topics include descriptive statistics, data
visualization techniques, an introduction to statistical inference (confidence intervals and
hypothesis testing) for decision making, linear regression models, data sampling techniques. The
students will learn the statistical package SPSS to analyze data sets from real-world
applications which will be discussed in class.
3 Credits -
MSIN 627
Multi-Dimensional Analytics and Visualization
- The course introduces the practice of managing data as corporate assets by organizations to gain
competitive advantage and meet regulatory demand. The course will also describe the data
management emerging profession, and skills required to perform the various data management
functions for each role.
Prerequisite: MSIN 615
3 Credits -
MSIN 637
Principles of Data Analytics
- This course is a hands-on introduction to the field of Data Analytics where students will learn
the concepts and tools needed throughout the analysis process from formulating the research
question to obtaining, cleaning, and collating data to making inferences and publishing results.
Students will also learn how to formulate research questions in “data terms” so that it can be
analyzed and identify the limitations imposed by the available data. Students will become versed
in sorting data, filtering data and creating data totals. They will learn how to use Pivot
Tables. They will also master Statistical Functions, Text Functions, Database Functions, Lookup
Functions, and Date and Time Functions among others. Students will be introduced to data types,
control structures, functions, and debugging tools. They will learn how to acquire data, what it
means to clean data by removing inconsistencies and reformat data so that it can be analyzed by
statistical tools.
Corequisite: MSIN 616
3 Credits
1
Thesis course required for both concentrations
-
MDAN 615
Data Analytics Internship
- This course provides students with the opportunity to work as an intern in the Data Analytics
area, and then to formulate a paper or project based on the approved internship. The internship
must be pre-approved and should provide the student with the ability to combine his/her
conceptual, technical, and applied knowledge in a business environment. This internship should
draw on the skills and knowledge gained throughout the program. Regular progress reporting is
expected throughout the internship. International students are required to apply for CPT for
eligibility to work during their internship. The Internship MUST be approved in advance by the
Program Chair. At the end of the internship, the student will be expected to take and pass a
recognized certification test to show competency in an aspect of Data Analytics.
Pre- or Corequisite: Permission of the Program Chair
3 Credits -
MDAN 617
Advanced Research in Data Analytics
- The Advanced Research course is designed to give students an individualized research, project
including reading and reporting on a specific topic approved by an instructor. The subject,
topics and related material must be relevant and advanced regarding data analytics either from a
technology perspective or from a business perspective depending on the student's area of
concentration.
3 Credits
Select One Concentration in M.S. in Data Analytics
See your selected concentration section to determine which required and elective courses you will need to take in your chosen area of study.