Business Analytics Certificate of Completion
Students seeking this certificate of completion will need to successfully complete:
(Click a course name below to view course details).
This course provides the theoretical basis and problem-solving experience needed to apply the techniques of descriptive and inferential statistics, to analyze quantitative data, and to improve decision making over a wide range of areas. Topics covered include descriptive statistics, linear regression, data gathering methodologies and probability, as well as confidence intervals and hypothesis testing for one and two samples. Use of technology in solving and interpreting statistical problems is emphasized. Prerequisite: MA 101 or placement via ALEKS Placement Assessment
This course offers an in-depth exploration of 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. A variety of topics are covered that include relational database model, data modeling, and database design.
This course introduces an analytical toolset to address business problems. The course provides an overview of the key concepts, applications, processes and techniques relevant to data modeling for business intelligence. The course makes use of SAS Enterprise Miner to illustrate the use of business analytics methodologies to enhance decision-making.
Skills learned in this course include:
- Artificial Neural Networks
- Business Analytics
- Business Intelligence
- Critical Thinking
- Data Modeling
- Decision Tree Learning
- Predictive Modeling
- Problem Solving
- Regression Analysis
- SAS (Software)
This course is designed to introduce students to the fundamentals of using Tableau Desktop in the context of business and data analytics. Students will learn to demonstrate data visualization in the data analysis process to efficiently wrangle and analyze real-industry data. Exploration of data as it relates to business requirements and business processes will include determining data quality criteria and data modeling techniques through the use of dashboards to create business intelligence.
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