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RSAN 101

Foundations of Data Science and Analytics

This course provides a foundation of the history, concepts, purpose and application of both data science and analytics in a business environment. This includes the methods of data collection, preparation, analysis, visualization, management, security and preservation of large sets of information. Also covered in the course are the primary methods of analytics, including predictive, prescriptive, and descriptive. The course will examine the various uses of analytics and how these methods identify and leverage competitive advantage in the era of ever-growing information requirements. The course will utilize case studies, trends, techniques, and best practices as it examines the topics of data science and analytics.
At the end of the course, students will be able to:
·Explain what data science and analytics are, including their history, purpose, and application in business
·Identify and assess the opportunities, needs and constraints for data collection, measurement, tracking, analysis, security, reporting and overall management within a strategic organizational context
·Describe the business issues that data science and analytics can address and resolve
·Identify the methods by which data can be collected, stored, secured, analyzed, interpreted, forecasted, visualized, reported and applied in a business environment
·Assess the most common challenges and issues that arise in the management of data
·Describe the various types of analytics, and the purpose of each in a business environment
·Describe how data science and analytics have developed and matured, and their likely paths over the next several years
·Describe the possible career choices in the areas of data science and analytics

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