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Exploratory Data Analysis

Master data visualization and exploration techniques using R's powerful plotting systems and statistical methods.

Master data visualization and exploration techniques using R's powerful plotting systems and statistical methods.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Specialization or Data Science: Foundations using R Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.7

(6,065 ratings)

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Instructors:

English

پښتو, বাংলা, اردو, 3 more

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Exploratory Data Analysis

This course includes

54 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Master R's plotting systems

  • Create effective data visualizations

  • Apply clustering techniques

  • Perform dimension reduction

  • Analyze multivariate data

  • Develop analytic graphics

Skills you'll gain

Data Visualization
R Programming
ggplot2
Lattice Graphics
Cluster Analysis
Dimension Reduction
Statistical Graphics
Exploratory Techniques
Base Plotting
Color Theory

This course includes:

5 Hours PreRecorded video

2 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

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Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 4 modules in this course

This comprehensive course teaches essential exploratory data analysis techniques for summarizing and understanding complex datasets. Students learn R's various plotting systems (base, lattice, and ggplot2), principles of data visualization, and advanced statistical methods including clustering and dimension reduction. The curriculum combines theoretical foundations with practical applications through case studies and hands-on programming exercises.

Week 1

Module 1 · 19 Hours to complete

Week 2

Module 2 · 16 Hours to complete

Week 3

Module 3 · 13 Hours to complete

Week 4

Module 4 · 5 Hours to complete

Fee Structure

Instructors

Brian Caffo
Brian Caffo

4.7 rating

20 Reviews

16,23,662 Students

30 Courses

Expert in Biostatistics and Neuroinformatics

Brian Caffo, PhD, is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He earned his PhD in Statistics from the University of Florida in 2001. Specializing in computational statistics and neuroinformatics, he co-created the SMART working group

Jeff Leek, PhD
Jeff Leek, PhD

4.7 rating

236 Reviews

16,66,593 Students

32 Courses

Chief Data Officer and J Orin Edson Foundation Chair at Fred Hutchinson Cancer Center

Dr. Jeff Leek serves as the Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics in Public Health Sciences at the Fred Hutchinson Cancer Center. Previously, he was a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. He earned his PhD in Biostatistics from the University of Washington and is known for his significant contributions to genomic data analysis and statistical methods for personalized medicine. His research has advanced our understanding of molecular mechanisms related to brain development, stem cell self-renewal, and immune responses to trauma, with findings published in top scientific journals such as Nature and Proceedings of the National Academy of Sciences. Dr. Leek developed a highly acclaimed Data Analysis course for Biostatistics students at Johns Hopkins, which has consistently received teaching excellence awards. He is also recognized for his efforts in creating educational initiatives that leverage data science for public health and economic development, including massive open online courses that have engaged millions worldwide.

Exploratory Data Analysis

This course includes

54 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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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.