Integrating Tableau and R for Data Science
This course provides an overview of how to combine Tableau and R to gain insights from data. Learn how to integrate these platforms and when to use each to maximize the potential of data science for your organization. ▼
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Course Feature
Cost:
Free Trial
Provider:
LinkedIn Learning
Certificate:
No Information
Language:
English
Course Overview
❗The content presented here is sourced directly from LinkedIn Learning platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course provides an overview of how to integrate Tableau and R for data science. Participants will learn how to connect Tableau to R, as well as when each platform is a better option. Additionally, the course will cover topics such as geocoding, running linear regression models, and clustering. By the end of the course, participants will have a better understanding of how to use Tableau and R together to analyze data.
[Applications]
After completing this course, participants can apply their knowledge of integrating Tableau and R for data science in a variety of ways. They can use Tableau to visualize data and R to perform statistical analysis, or use both platforms to create interactive dashboards. Participants can also use Tableau to geocode data, run linear regression models, and perform clustering. Additionally, they can use R to create custom visualizations and to access data from a variety of sources.
[Career Paths]
1. Data Scientist: Data Scientists use a combination of Tableau and R to analyze large datasets, identify trends, and develop predictive models. They are also responsible for creating visualizations to communicate their findings. As data becomes increasingly important in the business world, the demand for Data Scientists is expected to grow significantly.
2. Business Intelligence Analyst: Business Intelligence Analysts use Tableau and R to analyze data and develop insights that can be used to inform business decisions. They are responsible for creating dashboards and visualizations to communicate their findings. With the increasing demand for data-driven decision making, the demand for Business Intelligence Analysts is expected to grow.
3. Data Engineer: Data Engineers use Tableau and R to design and develop data pipelines and architectures. They are responsible for ensuring that data is collected, stored, and processed efficiently. As businesses become increasingly reliant on data, the demand for Data Engineers is expected to grow.
4. Data Visualization Developer: Data Visualization Developers use Tableau and R to create interactive visualizations and dashboards. They are responsible for designing and developing visualizations that are both visually appealing and informative. With the increasing demand for data-driven decision making, the demand for Data Visualization Developers is expected to grow.
[Education Paths]
1. Bachelor of Science in Data Science: This degree path focuses on the development of data-driven solutions to complex problems. Students learn to use a variety of tools and techniques to analyze data, develop predictive models, and create visualizations. As data science continues to grow in importance, this degree path is becoming increasingly popular.
2. Master of Science in Business Analytics: This degree path focuses on the application of data science to business problems. Students learn to use data to inform decisions, develop strategies, and optimize operations. This degree path is becoming increasingly popular as businesses look to leverage data to gain a competitive edge.
3. Master of Science in Artificial Intelligence: This degree path focuses on the development of intelligent systems that can learn from data and make decisions. Students learn to use machine learning algorithms, natural language processing, and other techniques to develop AI-driven solutions. As AI continues to become more prevalent, this degree path is becoming increasingly popular.
4. Doctor of Philosophy in Data Science: This degree path focuses on the development of advanced data science techniques. Students learn to use advanced statistical methods, machine learning algorithms, and other techniques to develop innovative solutions. This degree path is becoming increasingly popular as data science continues to evolve.
Course Syllabus
Where Tableau shines
Where R rules
Why integrate R and Tableau?
Course Provider
Provider LinkedIn Learning's Stats at AZClass
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Quiz
Submitted Sucessfully
1. What is the main purpose of this course?
2. What topics are covered in this course?
3. When is Tableau a better option than R?
4. What is the main benefit of integrating Tableau and R?
Correct Answer: Data Science
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