A leader in a data-driven world requires knowledge of statistical methods and appropriate models to analyze data. This course focuses on analytical frameworks for decision-making using Excel, covering linear and integer optimization, decision analysis, risk modeling, and more.
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This course comprises six modules that cover Excel basics, what-if analysis, decision analysis through regression and NPV, linear programming, transportation and assignment problems, and integer programming and nonlinear programming, offering a comprehensive journey from fundamental skills to advanced modeling techniques.
This module introduces Excel basics and best practices, from creating budgets to using formatting, formulas, and functions. Students will gain a solid foundation in Excel before moving on to more advanced analytical techniques.
Discover what-if analysis in Excel, including goal seeking, data tables, uncertainty, and more. Students will learn to apply these techniques to real-world business problems, such as determining break-even points and analyzing uncertainty.
Explore decision analysis through regression and net present value (NPV) calculations. Students will learn to model and evaluate decision alternatives, using regression to analyze trends and forecast future outcomes.
Learn about linear programming, including campaign marketing, investment allocation, and transportation problems. Students will apply solver tools in Excel to optimize resource allocation and solve complex business challenges.
This module covers transportation and assignment problems, including alternative Excel templates and real-world scenarios such as new hire assignments and MLB umpire assignments. Students will develop problem-solving skills for logistical challenges.
Delve into integer programming and nonlinear programming using real-world examples like project selection, portfolio variance, and investment decisions. Students will learn to use solver tools to optimize decision-making in complex business scenarios.
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