What you'll learn
- Non-mathematical data science principles
- Customer demand, marketing, new market forecasting, revenue projections, and data mining to improve decisions
- Methods that business leaders and data scientists have found to be the most useful.
- R for data mining
This course introduces non-mathematical business professionals to data science principles widely used in today's corporations. Quantitative methods affect many of today's interactions for business leaders, students, and consumers. Emphasis is placed on practical uses and case studies utilizing data to inform business decisions rather than theoretical or complex mathematics.
Case study topics include understanding customer demand, marketing, new market forecasting, revenue projections, and data mining to improve decisions. Learning goals include quantitative business application, basic programming, algorithm development, and process workflow.
The course highlights methods that business leaders and data scientists have found to be the most useful. It introduces the basic concepts of R for data mining. This course is for students who want an introduction to how data science improves business outcomes.
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