This specialization covers the foundations of visualization in the context of the data science workflow. Through the application of interactive visual analytics, students will learn how to extract structure from historical data and present key points through graphical storytelling. Additional topics include data manipulation, visualization foundations, audience identification, ethical considerations, dashboard creation, and report generation. Demonstrations of the basic visualization techniques used in Tableau will be included with a hands-on project.
Use Tableau for Your Data Science Workflow
University of California, Irvine via Coursera Specialization
Overview
Syllabus
Course 1: Data Visualization Best Practices
- Offered by University of California, Irvine. In this course, we will cover the basics of visualization and how it fits into the Data Science ... Enroll for free.
Course 2: Data Storytelling
- Offered by University of California, Irvine. This course will cover the more complex concepts that become involved when working beyond ... Enroll for free.
Course 3: Dashboarding and Deployment
- Offered by University of California, Irvine. This course will take you through the various parts of analytical dashboarding: from best ... Enroll for free.
- Offered by University of California, Irvine. In this course, we will cover the basics of visualization and how it fits into the Data Science ... Enroll for free.
Course 2: Data Storytelling
- Offered by University of California, Irvine. This course will cover the more complex concepts that become involved when working beyond ... Enroll for free.
Course 3: Dashboarding and Deployment
- Offered by University of California, Irvine. This course will take you through the various parts of analytical dashboarding: from best ... Enroll for free.
Courses
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In this course, we will cover the basics of visualization and how it fits into the Data Science workflow. We will focus on the main concepts behind the purpose of visualization and the design principles for creating effective, easy-to-communicate results. You will also set up your Tableau environment, practice data loading, and perform univariate descriptive analysis of the S&P 500 stock sectors.
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This course will cover the more complex concepts that become involved when working beyond simple datasets. Exploring the connection between visual aspects and data understanding, we will examine how those concepts work together through data storytelling. After reviewing key points on how to avoid problematic visualizations and data misrepresentation, you will continue working in Tableau performing multivariate descriptive analysis of the S&P 500 stock sectors.
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This course will take you through the various parts of analytical dashboarding: from best practices for designing a dashboard, creating a unified analytical environment, to deploying and publishing visualizations. We will briefly discuss the advanced visualization techniques and you will develop an information layout of the biggest gainers and losers in the financial markets and compare those movements to the economic data as your capstone project.
Taught by
Julie Pai and Majed Al-Ghandour
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Reviews
2.0 rating, based on 1 Class Central review
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These courses contain some interesting information and may be a great general-purpose, platform-agnostic data visualisation course. Unfortunately the course requires using Tableau, does not provide an access and also does not provide enough focus on it. It does not prepare you for a final assignment and a lot of people struggle to finish the specialisation because of that.
