Getting and Cleaning Data
This course is part of Data Science.
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 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.
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English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Obtain and manage data from various sources including web, APIs, and databases
Apply data cleaning techniques to create tidy datasets
Manipulate text and date data effectively using R
Work with different file formats and data storage systems
Use dplyr and other R packages for data manipulation
Skills you'll gain
This course includes:
3.3 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on the essential skills needed for data collection and cleaning in data science. Students learn to work with various data storage systems, including databases, APIs, and web sources. The curriculum covers making data "tidy," manipulating text and dates in R, and handling different data formats. Through hands-on exercises and practical applications, learners develop proficiency in data cleaning techniques and learn to prepare data for effective analysis.
Finding Data and Reading File Types
Module 1 · 2 Hours to complete
Data Storage Systems and Extraction
Module 2 · 1 Hours to complete
Organizing and Managing Data
Module 3 · 10 Hours to complete
Text and Date Manipulation
Module 4 · 5 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science
Instructors
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
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.
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