Business Analytics Certificate of Completion - Undergraduate
Students seeking this certificate of completion will need to successfully complete:
(Click a course name below to view course details).
MA 240 Applied Statistics
Provides the theoretical basis and the problem solving experience needed to apply the techniques of descriptive and inferential statistics, to evaluate such daily inputs as organizational reports and to improve decision making over a wide range of areas. Topics include: Descriptive Measures; Distribution Shapes; Concepts of Probability of Discrete and Continuous Random Variables; Hypothesis Testing of One, Two Samples; Chi-Square and F-Test; Regression; Anova; Using Excel, Minitab, TI 83+ or SPSS for Solving & Interpreting Statistical Problems. Prerequisite: MA101 (4 credit hrs)
In addition, students will select 9 credits (3 classes) from those below:
BAN 300 Base SAS Programming
This course is designed as the entry point to learning SAS programming, analytics programming concepts and environments. It provides the tools necessary to write SAS programs to perform data management, analysis, and reporting. The objective of this course is to provide the skills necessary to create and document data sets, manage and reshape data, write simple reports, and compute basic statistics on data set variables. Hands-on exercises designed to facilitate understanding of all the topics are included. The course also provides the basis for more advanced work in data analytics and advanced programming techniques for data management. This course aligns with the SAS Base Programming certification concepts. Prerequisite: MA 240
BAN 301 Enterprise Data and Information Management
This course offers an in-depth exploration of all the major topics in the field of data and information management from an applied perspective. The course is designed to provide not only a strong theoretical foundation, but also the technical skills required in analyzing, designing, implementing, managing, and utilizing information repositories. Topics covered include relational database model, data modeling, logical and physical database design, structured query language (SQL) implementation, procedures and triggers, data integration and quality, data warehouses and database administration. This course explores data and information management related issues in the context of business organizations; therefore, strategic roles that data and information play in business operations, customer relationship management, business decision-making, and strategy development are also discussed.
BAN 400 Introduction to Business Analytics
As the market demand for professionals with data management, analytical and problem-solving skills increases, this course provides an analytical toolset to address modern, data-intensive business problems. Using a case-based approach, the course provides an overview of the key concepts, applications, processes and techniques relevant to business analytics. The course makes use of the leading software products to illustrate the use of business analytics methodologies to enhance business decision-making. Anyone who is interested in learning how to make intelligent use of data in a proactive way to impact organizational performance, driving new behaviors from customers and suppliers, and stride ahead of the competition would benefit from this course. Prerequisite: BAN 300
BAN 401 Data Warehousing and Mining Applications
As business organizations collect more and more data as a byproduct of their operations, decision-makers are beginning to proactively and systematically analyze these data to improve decision quality. This course focuses on the two key processes of business analytics: data warehousing and data mining. The course provides an in-depth discussion on the modeling, design and implementation of data warehouses and other relevant techniques for addressing big data issues in organizations today. Data mining is the process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make proactive, knowledge-driven decisions. The course provides an in-depth discussion on various techniques of data mining including predictive modeling, pattern recognition, prescriptive analytics, and text mining. Both the theoretical and practical aspects of data warehousing and mining are discussed in this course. Prerequisite: BAN 400
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