Data Visualization with Tableau
Master data-driven decision making using Tableau to create impactful visualizations and uncover meaningful insights in this 4-week course.
Master data-driven decision making using Tableau to create impactful visualizations and uncover meaningful insights in this 4-week course.
Develop essential Tableau skills for data visualization and analysis in this comprehensive course. Learn to create compelling visual representations, interpret data accurately, and drive informed decision-making. With demand for Tableau expertise projected to grow 35% over the next decade, this course provides crucial skills for data-centric roles and career advancement.
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Instructors:
-1748521665388.webp&w=3840&q=75)
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What you'll learn
Create powerful data visualizations using Tableau's drag-and-drop interface
Design meaningful tables and graphs to effectively present data
Analyze and interpret data visualizations for accurate insights
Develop data-driven decision making skills using visual analytics
Identify and integrate key insights from complex data analysis
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive course teaches practical Tableau skills for effective data visualization. Students learn to explore data, create meaningful visual representations, and communicate insights effectively. The curriculum covers fundamental concepts of data representation, Tableau's drag-and-drop functionality, and best practices for creating accurate and impactful visualizations. Participants gain hands-on experience in creating various data representations while learning to evaluate and interpret visualizations for decision-making.
Fee Structure
Instructor
-1748521665388.webp&w=256&q=75)
2 Courses
Director of Academic and Faculty Affairs at Rochester Institute of Technology
As Director of Academic and Faculty Affairs for RIT Certified, Daniel loves helping bring to life the passion and expertise of subject matter experts in courses that help students advance their careers. As a math teacher for over a decade, he helped students think computationally and communicate their thinking using narratives, diagrams, code, or mathematical notation. In 2021, Daniel earned an MS in Data Science and joined RIT in 2022. Outside of work, he enjoys hiking, meditation, and RIT hockey.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.