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.
Introduction to Applied Business Analytics
Introduction to Applied Business Analytics
This course is part of multiple programs.
Instructor: Ronald Guymon
38,524 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.6
(285 reviews)
Beginner level
Recommended experience
Flexible schedule
1 week at 10 hours a week
Learn at your own pace
93%
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
Details to know
Shareable certificate
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Assessments
5 assignments
Taught in English
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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
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 videos7 readings2 assignments1 discussion prompt1 plugin
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
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
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
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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
4.6 (89 ratings)Offered by
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4.6
285 reviews
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Showing 3 of 285
BG
4
Reviewed on Aug 1, 2020
Very Helpful ,assignment section has made it more helpful
RS
5
Reviewed on Aug 3, 2023
Excellent content for someone with no background in R. The course is thoughtfully designed and well presented. I am willing to ignore a couple of minor issues I noticed.
N
5
Reviewed on Nov 12, 2024
A big Thumbs up to Professor Guymon for the fantastic knowledge transfer.
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