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Introduction to Business Analytics with R
  • Level Foundation
  • Duration 17 hours
  • Course by University of Illinois Urbana-Champaign
  • Offered by

About

Nearly every aspect of business is affected by data analytics. For businesses to capitalize on data analytics, they need leaders who understand the business analytic workflow. This course addresses the human skills gap by providing a foundational set of data processing skills that can be applied to many business settings. In this course you will use a data analytic language, R, to efficiently prepare business data for analytic tools such as algorithms and visualizations. Cleaning, transforming, aggregating, and reshaping data is a critical, but inconspicuous step in the business analytic workflow. As you learn how to use R to prepare data for analysis you will gain experience using RStudio, a powerful integrated development environment (IDE), that has many built-in features that simplify coding with R. As you learn about the business analytic workflow you will also consider the interplay between business principles and data analytics. Specifically, you will explore how delegation, control, and feasibility influence the way in which data is processed. You will also be introduced to examples of business problems that can be solved with data automation and analytics, and methods for communicating data analytic results that do not require copying and pasting from one platform to another.

Modules

About the Course

    • 2 Videos
    • 4 Readings
    • 1 Quiz
    • 1 Plugin
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2 Videos

  • Course Introduction
  • Meet Prof Ron Guymon

4 Readings

  • Syllabus
  • Glossary
  • About the Discussion Forums
  • Online Education at Gies College of Business

1 Quiz

  • Orientation Quiz

About Your Classmates

    • 1 Readings
    • 1 Discussion
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1 Discussions

  • Getting to Know Your Classmates

1 Readings

  • Update Your Profile

Module 1 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Introduction to Business Analytics and R

2 Readings

  • Module 1 Overview
  • Module 1 Readings

Module 1 Lectures

    • 10 Videos
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10 Videos

  • Overview of Business Analytics
  • Examples of Business Analytics
  • FACT Framework
  • Introduction to R
  • Getting Started with R
  • Calculations with R
  • Making Your Code Readable
  • Functions and Using the Built-In Help
  • Reading and Writing Data
  • Module 1 Conclusion

Module 1 Graded Activities

    • 1 Quiz
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1 Quiz

  • Module 1 Quiz

Module 2 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 2 Introduction

2 Readings

  • Module 2 Overview
  • Module 2 Readings

Module 2 Lectures

    • 13 Videos
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13 Videos

  • Is Data an Asset?
  • Properties of a Tidy Dataframe
  • Data Dictionaries
  • Getting to Know Your Data 1: Explore as in Excel
  • Getting to Know Your Data 2: Referring to Specific Rows and Columns
  • Summary Statistics
  • Getting to Know Your Data 3: Summary Statistics for Each Column, and Quick Plots
  • FACT Framework: Tell Others About The Results
  • R Notebooks
  • Markdown
  • Knitting Markdown Files
  • Dashboards Preview
  • Module 2 Conclusion

Module 2 Graded Activities

    • 1 Quiz
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1 Quiz

  • Module 2 Quiz

Module 3 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 3 Introduction

2 Readings

  • Module 3 Overview
  • Module 3 Readings

Module 3 Lectures

    • 11 Videos
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11 Videos

  • Assembling Data
  • Data Types
  • More on Functions
  • Packages
  • Introduction to Other Data Types
  • Creating Date Types
  • Calculations with Dates
  • Factors
  • Logical Type and Relational Operators
  • Character Strings
  • Module 3 Conclusion

Module 3 Graded Activities

    • 1 Quiz
    • 1 PeerReview
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1 Peer Review

  • Module 3 Peer Reviewed Assignment

1 Quiz

  • Module 3 Quiz

Module 4 Information

    • 1 Videos
    • 2 Readings
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1 Videos

  • Module 4 Introduction

2 Readings

  • Module 4 Overview
  • Module 4 Readings

Module 4 Lectures

    • 14 Videos
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14 Videos

  • Framing Questions for Actionable Insight
  • Dataframe Shape: Level of Aggregation
  • Dataframe: Control Versus Feasibility
  • Dataframe Shape: Wide Versus Long
  • Review of Notebooks and Introduction to dplyr
  • Subset Data Using dplyr's Select and Filter Functions
  • Useful Operators: %>% and %in%
  • Using dplyr's Mutate, Rename, Relocate, and Distinct Functions
  • Handling Missing Values
  • Data Aggregation and Summary
  • Pivoting Dataframes Between Wide and Long Shapes
  • Stacking and Sorting Data
  • Joining Data
  • Module 4 Conclusion

Module 4 Graded Activities

    • 1 Quiz
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1 Quiz

  • Module 4 Quiz

Course Wrap-up

    • 2 Videos
    • 2 Readings
    • 1 Plugin
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2 Videos

  • Gies Online Programs
  • Learn on Your Terms

2 Readings

  • Congratulations on completing the course!
  • Get Your Course Certificate

Auto Summary

Unlock the power of data with "Introduction to Business Analytics with R." Designed for aspiring data scientists and business leaders, this foundational course focuses on using R and RStudio to prepare business data for analysis. You'll learn essential skills in data cleaning, transforming, and visualization while exploring the integration of business principles with data analytics. Offered by Coursera, this 1020-minute course is perfect for beginners and is available with a Starter subscription.

Ronald Guymon
Instructors

Ronald Guymon

Ashish Khandelwal
Instructors

Ashish Khandelwal