This course provides an introduction to advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. Students are introduced to descriptive, predictive, prescriptive analytics, and optimization models. The course utilizes Microsoft Excel to engineer and analyze business models. Students identify the proper use of and complete regression, optimization, and exponential smoothing models.

Upon completion of this course, students are expected to be able to do the following:

• Utilize datasets to develop statistics and probability to predict future outcomes
• Implement appropriate models needed to analyze and critically evaluate business objectives
• Develop written and oral communication skills required to report on data-intensive business situations
• Organize data-intensive content in a professional setting
• Execute advanced analytics techniques

This course explores best-practice data visualization techniques. Professional storytelling and graphic design skills are introduced. Students study effective strategies and visualization tools to communicate with business decision makers.

Upon completion of this course, students are expected to be able to do the following:

• Source appropriate data to create effective visualizations
• Construct a compelling story with data to drive business action
• Design effective data visualizations in order to communicate information to the viewer
• Build visualizations that assist in error detection and data preparation

This course focuses on explaining complex datasets, models, and analysis to a variety of stakeholders including internal and external organizations and personnel of various disciplines. Audience analysis and effective strategic communication are studied. Students identify and analyze problems. Professionalism in both oral and written communication is expected.

Upon completion of this course, students are expected to be able to do the following:

• Conduct stakeholder analysis and communications results
• Identify business problems and create analytical approaches to solve them
• Write reports based on best-practice data analysis frameworks
• Demonstrate best practice communication techniques to visualize, explore, and act on data science findings

Prerequisite: BIA 630

This course introduces the concepts of spatial data creation, editing, and analysis using GIS software. Emphasis is placed on spatial concepts and understanding and utilizing standard operating procedures. Topics covered include coordinate systems, data creation, derivation, editing, metadata, proximity and overlay analysis, and cartography. Technical proficiency is a primary objective of the course, reinforced by significant practical exercises utilizing GIS software. Examples of how the geospatial industry provides location intelligence to a variety of disciplines are explored.

Upon completion of this course students are expected to be able to do the following:

• Apply knowledge of principles, theories, and concepts of spatial data analysis
• Demonstrate standard techniques for creating, editing, storing, querying, and analyzing geospatial data
• Use cartographic design principles for visual storytelling and effective communication
• Implement practices to promote spatial data integrity based on an understanding of sources of error in spatial data