Tools for Exploratory Data Analysis in Business
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Tools for Exploratory Data Analysis in Business
This course is part of Business Analytics Specialization
Instructors: Ronald Guymon
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What you'll learn
Development of an analytic mindset for approaching business problems.
The ability to appraise the value of datasets for addressing business problems using summary statistics and data visualizations.
Competence in operating business analytic software applications for exploratory data analysis.
Skills you'll gain
Tools you'll learn
Details to know
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There are 4 modules in this course
This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using Python to conduct the ETL and EDA processes.
The learning outcomes for this course include: 1. Development of an analytic mindset for approaching business problems. 2. The ability to appraise the value of datasets for addressing business problems using summary statistics and data visualizations. 3. The ability to competently operate business analytic software applications for exploratory data analysis.
Your mind is the most important tool. Prepare your mind by learning about various mindsets and terms for approaching business analytic problems.
What's included
14 videos8 readings2 assignments1 discussion prompt1 plugin
14 videos•Total 84 minutes
- Course Introduction•4 minutes
- About Professor Kim Mendoza•2 minutes
- About Professor Ronald Guymon•3 minutes
- The Impact of the Gies Community•2 minutes
- Business Analytics Key Terms•11 minutes
- Module 1 Introduction•4 minutes
- Turning Business Data Into Business Insights•13 minutes
- Your Mind is the Most Important Tool•6 minutes
- Analytics Mindset: System 1 vs. System 2•11 minutes
- Analytics Mindset: Inductive Versus Deductive Reasoning•7 minutes
- Analytics Mindset: Let the Data Speak•8 minutes
- Introduction to the Course Data Set, TECA•5 minutes
- The FACT Framework•7 minutes
- Module 1 Conclusion•2 minutes
8 readings•Total 80 minutes
- Syllabus•10 minutes
- Coursera Coach•10 minutes
- About the Discussion Forums•10 minutes
- Online Education at Gies College of Business•10 minutes
- Updating Your Profile•10 minutes
- Module 1 Overview•10 minutes
- Module 1 Optional Readings•10 minutes
- Module 1 Study Guide•10 minutes
2 assignments•Total 90 minutes
- Analytics Mindset: Quiz•60 minutes
- Orientation Quiz•30 minutes
1 discussion prompt•Total 10 minutes
- Getting to Know Your Classmates•10 minutes
1 plugin•Total 15 minutes
- Demographics Survey•15 minutes
Python is a powerful tool for working with data. In this module, we will use Python to extract, transform, and load data, generate summary statistics and visualizations for exploration, and understand the value of performing data analysis directly within Python.
What's included
13 videos3 readings1 assignment
13 videos•Total 169 minutes
- Module 2 Introduction•5 minutes
- Data•5 minutes
- Business Problem•3 minutes
- Installation Demonstration•11 minutes
- Intro to Jupyter Lab and Using AI•16 minutes
- Loading and Viewing the Data•17 minutes
- Optional Video: Data Types•18 minutes
- Data Cleaning•30 minutes
- Optional Video: Joining Data•12 minutes
- Optional Video: Summarizing Data•15 minutes
- Intro to Python Library for Visualization•14 minutes
- Creating Visualizations in Python•19 minutes
- Module 2 Conclusion•4 minutes
3 readings•Total 30 minutes
- Module 2 Overview•10 minutes
- Module 2 Files•10 minutes
- Module 2 Study Guide•10 minutes
1 assignment•Total 60 minutes
- ETL and EDA Using Python: Quiz•60 minutes
In this module, we will explore how data quality impacts business analytics, examine the relationship between data transformation and managerial decision-making, and develop foundational skills in data manipulation using dplyr, tidyr, and stringr to prepare data for visualization.
What's included
11 videos3 readings1 assignment1 peer review
11 videos•Total 75 minutes
- Module 3 Introduction•3 minutes
- Introduction to Databases•7 minutes
- Overview of Structured Query Language (SQL)•8 minutes
- Basic SQL Commands•12 minutes
- Why Do We Need SQL and Python?•9 minutes
- Connecting and Disconnecting to a Database in Python•7 minutes
- Basic SQL Workflow in Python•6 minutes
- SQLite Exploratory Queries in Python•7 minutes
- SQL Descriptive Queries in Python•6 minutes
- SQL Join Queries in Python•7 minutes
- Module 3 Conclusion•3 minutes
3 readings•Total 30 minutes
- Module 3 Overview•10 minutes
- Module 3 Files•10 minutes
- Module 3 Study Guide•10 minutes
1 assignment•Total 60 minutes
- ETL and EDA Using SQL: Quiz•60 minutes
1 peer review•Total 180 minutes
- ETL and EDA Using Python: Peer Reviewed Assignment•180 minutes
In this module, we will learn to execute effective data visualizations using Dona Wong’s framework, craft emotionally resonant and visually clear charts, and apply advanced techniques to enhance the clarity, sophistication, and storytelling power of our data visuals.
What's included
13 videos5 readings1 assignment1 discussion prompt1 plugin
13 videos•Total 86 minutes
- Module 4 Introduction•5 minutes
- What are APIs?•7 minutes
- Web APIs for Assembling Data•8 minutes
- Key Elements of API Requests and Responses•10 minutes
- Building API Requests with the Requests Module•13 minutes
- Building API Requests that Require Authentication•5 minutes
- Building API Requests with Software Development Kits•5 minutes
- Loops•8 minutes
- Loops and APIs•7 minutes
- API for ChatGPT•10 minutes
- Strategies for Working with Web APIs•3 minutes
- Module 4 Conclusion•6 minutes
- Learn on Your Terms•1 minute
5 readings•Total 50 minutes
- Module 4 Overview•10 minutes
- Module 4 Files•10 minutes
- Module 4 Study Guide•10 minutes
- Congratulations on completing the course!•10 minutes
- Get Your Course Certificate•10 minutes
1 assignment•Total 30 minutes
- ETL and EDA Using APIs: Quiz•30 minutes
1 discussion prompt•Total 10 minutes
- Reflection•10 minutes
1 plugin•Total 15 minutes
- Course End Survey•15 minutes
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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
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Reviewed on Aug 15, 2022
Good course. I could make my first step with Alteryx. Thanks. I just regret that the assignement is not on Alteryx.
Reviewed on Mar 2, 2023
Great course, I appreciate both instructors for this informative course!
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