Predictive Analytics and Data Visualization Graduate Certificate

Graduate Certificate (12 credits)

Graduate Certificates provide students with the opportunity to deepen their skills in a particular subject. They may be completed at any time while taking Master of Business Administration courses provided the prerequisites are met, or may be completed as a stand-alone certificate.

The credit for a single course cannot be applied to more than one degree or certificate; a course substitution must be approved by the Department Chair.

Recommended Prerequisite: DATA610 Essentials of Business Analytics (3 cr) is a recommended prerequisite that should be completed prior to taking the following courses in the Graduate Certificate in Predictive Analytics and Data Visualization.

*DATA courses are only offered in a 15-week online format.

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Major		12 Credits
DATA667	Data Visualization & Commnctn Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruc-tion is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner.	3
DATA710	Introduction to R Programming The basics of R programming are introduced including software installation and configuration necessary for effective data analysis. Generic programming language concepts are introduced and covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based introduction of programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples.	3
DATA772	Stat Analysis Data Analytics This course covers statistical procedures used in data analytics with emphasis on hands-on practice. Industry standard software is used to import and prepare data for model development as well as for developing various types of regression models. Assessment of model performance and methods for model selection are also covered. Emphasis is also placed on parameter estimation, variable selection, and diagnostic checking of these models and their use for statistical inference and prediction. Both numerical and graphical techniques are used for diagnostics and reporting. Prerequisite(s): DATA710	3
DATA785	Predictive Modeling This course covers statistical modeling in the use of statistical methods to develop models that can be used for predicting future numerical or categorical out-comes in processes for disciplines ranging from business to science. The philosophy of modeling as well as common modeling methods and model adequacy assessment procedures are covered. Industry standard software is used to prepare data, develop and assess models, obtain predictions, and present results. The main thrust of the course is on the application of predictive modeling rather than the theory behind it. Selected projects will be used to provide hands-on experience with the various steps involved in modeling and predicting. Prerequisite(s): DATA772	3

Which class should I take? When should I take it?

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Classes are being offered on-campus and online for the fall semester

Predictive Analytics and Data Visualization Graduate Certificate

Predictive Analytics and Data Visualization Graduate Certificate

Major

Which class should I take? When should I take it?

Course Description