What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Introduction to Applied Business Analytics

Seize the savings! Get 40% off 3 months of Coursera Plus and full access to thousands of courses.

Introduction to Applied Business Analytics

This course is part of multiple programs.

Instructor: Ronald Guymon

43,158 already enrolled

Included with

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

319 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

319 reviews

Beginner level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

94%

Most learners liked this course

What you'll learn

Examine the interplay between business principles and data analytics.
Build a foundation in data analytics by installing and using a data analytics language, an integrated development environment (IDE), and key modules.
Manipulate the most commonly used data types using functions.
Develop efficient, easy-to-read approaches for assembling and processing data for analysis.

Skills you'll gain

Tools you'll learn

Python Programming

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

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 Python, a widely adopted data analytics language, 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 Python to prepare data for analysis, you will gain experience using integrated development environments (IDEs) that simplify coding, support data exploration, and help you share results effectively. As you learn about the business analytics 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.

In this module, you will be introduced to (1) the FACT framework for approaching business analytics, and (2) Python and the use of JupyterLab or Google Colab for running basic analyses.

What's included

20 videos8 readings2 assignments1 discussion prompt1 plugin

20 videos Total 118 minutes

Course Introduction 5 minutes
Meet Professor Ron Guymon 4 minutes
The Impact of the Gies Community 2 minutes
Module 1 Introduction 7 minutes
Overview of Business Analytics 4 minutes
Examples of Business Analytics 8 minutes
FACT Framework 8 minutes
Why Python for Business Analytics? 1 minute
Python Accoutrements 4 minutes
Python and Integrated Development Environments (IDEs) 7 minutes
Installing Python Using JupyterLab Desktop (Recommended for Windows and Mac Users) 6 minutes
Installing Python Using Homebrew and Pyenv (For advanced Mac users) 7 minutes
Installing Python from Python.org for Windows (For advanced Windows users) 5 minutes
An Example Workflow With JupyterLab 9 minutes
Tour of JupyterLab 8 minutes
Using Interactive Python Notebook (IPYNB) Files 9 minutes
Tour of Jupyter Notebook 3 minutes
Basic Calculations with Python 8 minutes
Google Colab - An Online Version of Jupyter Notebook 9 minutes
Module 1 Conclusion 3 minutes

8 readings Total 80 minutes

Syllabus 10 minutes
Glossary 10 minutes
About the Discussion Forums 10 minutes
Online Education at Gies College of Business 10 minutes
Update Your Profile 10 minutes
Module 1 Overview 10 minutes
Module 1 Readings 10 minutes
Installing Python and JupyterLab: Start Here 10 minutes

2 assignments Total 30 minutes

Orientation Quiz 0 minutes
Module 1 Quiz 30 minutes

1 discussion prompt Total 10 minutes

Getting to Know Your Classmates 10 minutes

1 plugin Total 15 minutes

Welcome! Please Tell Us About Yourself 15 minutes

In this module, you’ll focus on framing clear, purposeful questions—whether you're identifying business problems or writing Python code. You’ll explore strategies for troubleshooting and gathering help from various sources, including AI tools, built-in documentation, and error messages. You’ll also be introduced to foundational Python data structures like DataFrames, dictionaries, lists, and strings.

What's included

14 videos2 readings1 assignment

14 videos Total 85 minutes

Module 2 Introduction 4 minutes
Framing Questions for Actionable Insight 8 minutes
Framing Python Questions 14 minutes
Framing Questions for External Sources 9 minutes
Framing Questions for Python's Built-In Documentation 6 minutes
Framing Questions About Module Functions and Methods 5 minutes
Framing Questions About Pandas Dataframes 8 minutes
Framing Questions About Python Dictionaries 5 minutes
Framing Questions About Python Lists 4 minutes
Framing Questions About Python Strings 7 minutes
Acting on the Answer 3 minutes
Acting on the Answer by Running Code Experiments 7 minutes
Acting on the Answer by Reading Error Messages 5 minutes
Module 2 Conclusion 3 minutes

2 readings Total 20 minutes

Module 2 Overview 10 minutes
Module 2 Readings 10 minutes

1 assignment Total 30 minutes

Module 2 Quiz 30 minutes

In this module, you will learn about tidy data and then gain practice using basic exploratory techniques for evaluating the tidiness of pandas DataFrames. Specifically, you’ll first learn various approaches for filtering data to specific rows and columns. You’ll then learn how to explore the data using descriptive statistics and visualizations. By mastering these techniques, you'll be equipped to efficiently identify the value of real-world data and the potential of that data for providing insight to the business questions that have been framed.

What's included

12 videos2 readings1 assignment1 peer review

12 videos Total 106 minutes

Module 3 Introduction 3 minutes
Is Data an Asset? 7 minutes
Assembling Data 7 minutes
Properties of a Tidy Dataframe 5 minutes
Data Dictionaries 5 minutes
Characteristics of a Tidy Dataset 13 minutes
Exploring Dataframes Using Filters 10 minutes
Exploring Dataframes Using Conditional Statements 13 minutes
Summary Statistics 12 minutes
Exploring Data with Summary Statistics 12 minutes
Exploring Dataframes with Visualizations 16 minutes
Module 3 Conclusion 3 minutes

2 readings Total 20 minutes

Module 3 Overview 10 minutes
Module 3 Readings 10 minutes

1 assignment Total 30 minutes

Module 3 Quiz 30 minutes

1 peer review Total 120 minutes

Module 3 Peer Reviewed Assignment 120 minutes

In this module, you’ll clean and prepare data using core Python and pandas tools. Through hands-on examples, you’ll fix issues like missing values and formatting problems, organize data into a tidy structure, write clear and efficient code, and save data in a more compact format that preserves the cleaned data.

What's included

13 videos4 readings1 assignment1 plugin

13 videos Total 87 minutes

Module 4 Introduction 5 minutes
Cleaning and Preprocessing the Data 9 minutes
General Data Cleaning Tasks for Columns of a Dataframe 6 minutes
General Data Cleaning Tasks for Rows of a Dataframe 10 minutes
Cleaning String Columns of a Dataframe 13 minutes
Cleaning Date Columns of a Dataframe 11 minutes
Dataframe Shape: Wide Versus Long 4 minutes
Changing the Shape of a Dataframe 5 minutes
Combining Dataframes 9 minutes
Cleaning Your Code 6 minutes
Saving Cleaned Data 7 minutes
Module 4 Conclusion 2 minutes
Learn on Your Terms 1 minute

4 readings Total 40 minutes

Module 4 Overview 10 minutes
Module 4 Readings 10 minutes
Congratulations on completing the course! 10 minutes
Get Your Course Certificate 10 minutes

1 assignment Total 30 minutes

Module 4 Quiz 30 minutes

1 plugin Total 15 minutes

How Was the Course? 15 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Build toward a degree

This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

Instructor

Instructor ratings

(99 ratings)

Ronald Guymon

University of Illinois Urbana-Champaign

5 Courses 90,553 learners

Offered by

University of Illinois Urbana-Champaign

Explore more from Business Essentials

Status: Free Trial
Tableau Learning Partner
Introduction to Business Analytics
Course
Status: Free Trial
Coursera
Applying Python for Data Analysis
Course
Status: Preview
Campus BBVA
Business Analytics
Course
Status: Free Trial
University of Illinois Urbana-Champaign
Accounting Data Analytics with Python
Course

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

5 stars
75.86%
4 stars
17.24%
3 stars
3.13%
2 stars
0.94%
1 star
2.82%

Showing 3 of 319

Reviewed on Dec 13, 2020

This course is well designed for newbies like me and our teachers are super dedicated.

Reviewed on Jan 21, 2026

Very easy to follow and very straightforward, easy to understand

Reviewed on Sep 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.

View more reviews

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Learn more

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Explore degrees

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Learn more

Frequently asked questions

Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). If you choose to explore the course without purchasing, you may not be able to access certain assignments.

You will be eligible for a full refund until 2 weeks after your payment date. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the 2-week refund period. View our full refund policy.

Yes! Coursera provides financial aid to learners who would like to complete a course but cannot afford the course fee. To apply for aid, select "Learn more and apply" in the Financial Aid section below the "Enroll" button. You'll be prompted to complete a simple application; no other paperwork is required.