Free Business Analytics Excel course Elementary to Advanced with Certificate
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In today's data-driven world, a successful leader needs to possess knowledge of statistical methods as well as appropriate models to interpret and utilize data. The Business Analytics course emphasizes on the latter aspect, introducing students to analytical frameworks that aid decision-making through Excel modeling. These frameworks include Linear and Integer Optimization, Decision Analysis, and Risk modeling.
The focus of the course is not solely on Excel's "how-to", but on the formulation of problems, transforming the problems into useful models, optimizing and/or displaying the models, and interpreting the results. The curriculum is designed to equip managers with the ability to translate trade-offs into models, comprehend the output of the software, and understand the significance of quantitative approaches in decision-making.
Business analytics relies heavily on data and modeling to facilitate decision-making within organizations. This course aims to introduce students to analytical frameworks that make sense of data, starting with the basics of Excel and advancing towards more complex modeling techniques.
Syllabus
Introduction to Excel: Basics and Best Practices
In this course, you will learn about management science methods and how to model them in Excel to solve various problems. The course starts with the basics of spreadsheet design and gradually progresses to more complex mathematical optimization modelling. The skills and techniques taught in this course are essential for many industries such as airlines, banks, and technology companies. The first module introduces a simple example of a mathematical model that will serve as the foundation for more advanced applications in later modules.
What-If Analysis in Excel
In this module, we will delve into advanced techniques for creating spreadsheet models. We understand that learners come from different backgrounds, and therefore, we will provide a review of basic functions and features before introducing more complex concepts. Our objective is to help learners develop a comprehensive understanding of the modelling process and equip them with knowledge of less-familiar but useful Excel functions and tools. However, it is important to note that this course is not intended to be a comprehensive guide to Excel. Rather, our focus is on using these features to gain insights into real-world business problems.
Decision Analysis through Regression and NPV
This module delves into the concept of estimating relationships between variables through curve fitting or regression analysis to address practical business problems. The module introduces various regression curves and presents a mathematical analysis to determine the best curve to support the model. Through this approach, students gain an understanding not only of the techniques of modeling but also the rationale for selecting a particular model.
Linear Programming
This module focuses on introducing students to linear programming (LP) as a powerful method of quantitative analysis. LP is widely used in various organizations to solve different kinds of problems, such as labor scheduling, inventory management, advertising, finance, transportation, staffing, and more. Through the examples presented in this course, students will learn the basic concepts of LP, the types of problems it can solve, and how to model an LP problem in Excel. The objective is to provide students with the fundamental skills necessary to apply LP to real-world business problems.