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This course is designed to equip you with practical and hands-on knowledge of business analytics, covering the three main categories of descriptive, predictive, and prescriptive analytics. We will begin by delve into data preprocessing using Tableau, where you will learn how to transform and manipulate data for analysis. You will also learn about storytelling with dashboard visualizations, clustering, text mining, and association rules, all of which are part of descriptive analytics. We will then explore several predictive modeling techniques, including linear regression, logistic regression, K-Nearest Neighbors, and classification trees, which are part of predictive analytics. We will use Microsoft Excel to build models that predict outcomes and make data-driven decisions. Lastly, we will cover prescriptive analytics, where you will learn how to use optimization techniques such as Linear Programming, Integer Programming, Decision Trees, and Monte Carlo Simulation to make optimal business decisions. By the end of the course, you will have the necessary skills to analyze and interpret data, build predictive models, and make optimal business decisions using various techniques of business analytics.