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Pre-MBA Quantitative Skills: Data Analysis
  • Level Foundation
  • Duration 19 hours
  • Offered by

About

This course will equip students with the quantitative skills needed to begin any Masters of Business Administration program. The goal is not to build foundational skills or expert mastery but rather, to provide some middle ground to “shake the rust off” skills that a typical MBA student probably knows, but may not have thought about for quite some time. The course provides a quick refresher on top level math and statistics concepts that will be used throughout the MBA curriculum at any school. All of the concepts will be reinforced with practical real-world examples. All calculations, formulas, and data analysis will be performed in Excel, with many detailed demonstrations. For those unfamiliar or less comfortable with spreadsheets, the course will also prepare students with a basic facility for using spreadsheets to solve quantitative business problems. This course has no prerequisites and is intended for any audience.

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Embark on your MBA journey with confidence by enrolling in "Pre-MBA Quantitative Skills: Data Analysis," a comprehensive course offered by Coursera. This foundational program is meticulously designed to refresh your quantitative skills, ensuring you're well-prepared for the rigorous demands of any MBA curriculum. Focusing on essential math and statistics concepts, this course delivers practical, real-world examples to reinforce learning. You'll gain proficiency in Excel, mastering the calculations, formulas, and data analysis techniques crucial for solving business problems. With a commitment of just over 19 hours, this course is accessible to all, requiring no prior knowledge or prerequisites. The Starter subscription option makes it easy to get started on your path to success. Ideal for prospective MBA students or anyone looking to bolster their quantitative skills, this course offers the perfect blend of theory and application to help you thrive in your academic and professional pursuits.