M.S. Data Analytics Areas of Study

Master of Science in Data Analytics

The MSDA degree prepares experienced and successful software developers and information technology professionals for productive careers as data analysts. It offers data mining and analytics courses that prepare graduates for applying advanced techniques in statistical analysis, data analytics, data manipulation, and advanced data visualization.

Data Analytics

Fundamentals of Data Analytics
This course introduces you to the basic concepts of data analytics, data mining, and spreadsheet models. These basic statistical concepts will prepare you to support analytic tools and will prepare you for advanced analytic methods. Analytical approaches in the area of data-driven decision making processes will be explored.

Statistics for Data Analysis
This course covers a broad range of statistical techniques and methods applied in real-world settings. Topics presented include inferential, parametric and non-parametric statistics, as well as regression analysis and analysis of variance.

Data Mining and Analytics I
This course is an introduction to data mining and exploratory data analysis, including text and web mining. Topics include the use of data exploration methods to prepare data, familiarization with commercial data types commonly used for data mining, the use of statistical and data mining software, including R, SAS and SPSS, and the comparison and classification of data mining methods.

Data Mining and Analytics II
This course examines the application of descriptive and predictive data mining techniques to reveal information within a mass of data. Techniques include factor analysis, cluster analysis, classification methods, and neural networks to limit human subjectivity in decision making processes.

Advanced Data Visualization
The focus of this course is visualizing and telling stories with data. This course begins with a description of the growth of data and visualization in industry, news, and government. Actual human stories will be reviewed from a data-statistical perspective. The creation of graphs, displays and geospatial data presentations to communicate information supporting decision making while implementing best practices for effective storytelling will be examined.

Advanced SQL
This course prepares the student for the Oracle SQL Expert Certification (1Z0-047). Students will master the SQL language to restrict and sort data, manage data, objects and tables, create schema objects, and control user access.

SAS Programming I: Fundamentals
This course prepares programmers, analysts, and data managers to access and manage data using SAS tools to perform queries and analyses that lead to certifications.

SAS Programming II: Business Analysis Applications
This course is designed for professionals who solve business problems by performing statistical analyses and predictive modeling using SAS.

Data Analytics Graduate Capstone

Data Science

Data Science Tools and Techniques
This course covers data science tools and techniques to perform data wrangling and exploration. You will be introduced to programming languages and web scraping tools along with machine learning models.

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