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Part of the Master of Science in Accountancy (iMSA) degree

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Introduction to Business Analytics with R

University of Illinois at Urbana-Champaign

About this Course

178,666 recent views

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.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

At least 1 year of business experience. Critical thinking.

Approx. 15 hours to complete

English

Subtitles: English

What you will learn

You will learn how to process data using R and RStudio. You will also explore the interaction between business principles and data analytics.

Skills you will gain

Business AnalyticsR ProgrammingRstudio

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

At least 1 year of business experience. Critical thinking.

Approx. 15 hours to complete

English

Subtitles: English

Instructors

Instructor rating

4.44/5 (31 Ratings)

Ronald Guymon
Top Instructor

Senior Lecturer of Accountancy

Accountancy

28,511 Learners

4 Courses

Ashish Khandelwal

Adjunct Professor

Business Administration

7,820 Learners

1 Course

Offered by

University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Accountancy (iMSA) from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

Learn More

Syllabus - What you will learn from this course

Week

Week 1

4 hours to complete

Course Overview and Module 1 How Do I Get Started Using a Data Analytic Language to Solve Business Problem?

In this module you will be introduced to (1) the role of data analytics in business domains, and (2) R and RStudio.

4 hours to complete

13 videos (Total 84 min), 5 readings, 2 quizzes

13 videos

Course Introduction4m

Meet Prof Ron Guymon2m

Introduction to Business Analytics and R6m

Overview of Business Analytics3m

Examples of Business Analytics5m

FACT Framework7m

Introduction to R6m

Getting Started with R5m

Calculations with R12m

Making Your Code Readable4m

Functions and Using the Built-In Help8m

Reading and Writing Data12m

Module 1 Conclusion1m

5 readings

Syllabus10m

About the Discussion Forums10m

Glossary10m

Module 1 Overview10m

Module 1 Readings1h

2 practice exercises

Orientation Quiz

Module 1 Quiz30m

Week

Week 2

2 hours to complete

Module 2 How Do I Get to Know My Data and Share It with Others?

In this module you will explore whether data is an asset and how to explore a dataset.

2 hours to complete

13 videos (Total 90 min), 2 readings, 1 quiz

13 videos

Module 2 Introduction2m

Is Data an Asset?5m

Properties of a Tidy Dataframe4m

Data Dictionaries4m

Getting to Know Your Data 1: Explore as in Excel4m

Getting to Know Your Data 2: Referring to Specific Rows and Columns7m

Summary Statistics12m

Getting to Know Your Data 3: Summary Statistics for Each Column, and Quick Plots6m

FACT Framework: Tell Others About The Results6m

R Notebooks11m

Markdown7m

Dashboards Preview13m

Module 2 Conclusion3m

2 readings

Module 2 Overview10m

Module 2 Readings10m

1 practice exercise

Module 2 Quiz30m

Week

Week 3

6 hours to complete

Module 3 How Can I Use Functions to Help with Data Preparation?

This module starts with a discussion on the importance of assembling data for business analytic purposes, and then illustrates data transformation using Tidyverse, a group of useful R packages.

6 hours to complete

12 videos (Total 107 min), 2 readings, 2 quizzes

Week

Week 4

3 hours to complete

Module 4 How Do I Preprocess Data?

In this module, we will learn how delegation, feasibility, and control influence the level at which data is aggregated. We then focus on performing a variety of data preprocessing tasks to prepare data for use in visualizations and algorithms.

3 hours to complete

16 videos (Total 92 min), 2 readings, 1 quiz

16 videos

Module 4 Introduction3m

Module 4 Introduction51s

Framing Questions for Actionable Insight7m

Dataframe Shape: Level of Aggregation3m

Dataframe: Control Versus Feasibility5m

Dataframe Shape: Wide Versus Long3m

Review of Notebooks and Introduction to dplyr3m

Subset Data Using dplyr's Select and Filter Functions7m

Useful Operators: %.% and %in%7m

Using dplyr's Mutate, Rename, Relocate, and Distinct Functions10m

Handling Missing Values6m

Data Aggregation and Summary4m

Pivoting Dataframes Between Wide and Long Shapes6m

Stacking and Sorting Data7m

Joining Data8m

Module 4 Conclusion3m

2 readings

Module 4 Overview10m

Module 4 Readings40m

1 practice exercise

Module 4 Quiz30m

Reviews

4.5

26 reviews

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4 stars
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3 stars
3.96%
2 stars
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1 star
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TOP REVIEWS FROM INTRODUCTION TO BUSINESS ANALYTICS WITH R

by NPMay 12, 2020

This class was great, you get to learn the basics of R, I have no previous experience with programming languages and I feel in a much better place, after taking this class. I highly recommend it.

by DRJun 13, 2020

Thank you for helping me in acquiring the knowledge of the analysis using the R studio. I have really got a good understanding of how does this is been applied in an organisation.

by ETSep 13, 2020

first part was easy to follow and last 2 week courses were too much focused on getting code drilled and not enough on what the code could be used for in real life.

by PPAug 13, 2020

Excellent, very intuitive course, a good way to start your journey with R and analytic career.

View all reviews

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Introduction to Business Analytics with R

Introduction to Business Analytics with R