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Business Analytics Certificate of Completion - Graduate

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)
    University Syllabus

In addition, students will select 9 credits (3 classes) from those below:

  • BAN 500 SAS Programming for Business Analytics

    This course is designed to provide a foundation of SAS analytics programming concepts and environments. It provides the tools necessary to write SAS programs to perform data management, analysis, and reporting. Topics include creating and documenting data sets, managing and reshaping data, writing reports, computing statistics on data set variables, and performing effective SAS programming. 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 offered through the SAS Institute, Inc. Prerequisite: MA 240 or equivalent
    University Syllabus

  • BAN 520 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 with an emphasis on data warehouses. 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 other relevant techniques for addressing big data issues in organizations today. The strategic roles that data and information play in business operations, customer relationship management, business decision-making, and strategy development are also discussed.
    University Syllabus

  • BAN 600 Advanced 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. To be effective in a competitive business environment, a business analytics professional needs to be able to use analytical tools to translate information into decisions and to convert information about past performance into reliable forecasts. 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. Prerequisite: BAN 520, For MSMIS students: Completion of CIS 628 satisfies this prerequisite.
    University Syllabus

  • BAN 620 Advanced Data 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 topics relevant to data mining, which 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 mining are discussed in this course. Prerequisite: BAN 600.
    University Syllabus

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