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Chris Shockley
Congratulations you've made it to Part 2 of the DPLYR series! In a moment you will be taken to Rhyme where a Virtual Machine with R, R Studio and DPLYR awaits. Once there you will begin the Project where you will be introduced to the Rhyme Interface and subsequently learn how to use the DPLYR verbs in a more advanced way by building on the foundation learned in the previous course. Come in, get experience using R and learn new ways to use the dplyr functions.
Read more
Congratulations you've made it to Part 2 of the DPLYR series! In a moment you will be taken to Rhyme where a Virtual Machine with R, R Studio and DPLYR awaits. Once there you will begin the Project where you will be introduced to the Rhyme Interface and subsequently learn how to use the DPLYR verbs in a more advanced way by building on the foundation learned in the previous course. Come in, get experience using R and learn new ways to use the dplyr functions.
Read more
Congratulations you've made it to Part 2 of the DPLYR series! In a moment you will be taken to Rhyme where a Virtual Machine with R, R Studio and DPLYR awaits. Once there you will begin the Project where you will be introduced to the Rhyme Interface and subsequently learn how to use the DPLYR verbs in a more advanced way by building on the foundation learned in the previous course. Come in, get experience using R and learn new ways to use the dplyr functions.
By the end of this course, you will be able to:
To practice the basic dplyr functions and how they are used
To learn advanced features of the dplyr verb 'mutate'
To implement the verb mutate over a data set in place of a 'for loop'
To continue thinking in dplyr verb phrases (ex. filter, aggregate, and transform data)
Register for this course and see more details by visiting:
OpenCourser.com/course/9nl4kq/build
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What's inside
Syllabus
Intro to DPLYR Part 2
Congratulations you've made it to Part 2 of the DPLYR series! In a moment you will be taken to Rhyme where a Virtual Machine with R, R Studio and DPLYR awaits. Once there you will begin the Project where you will be introduced to the Rhyme Interface and subsequently learn how to use the DPLYR verbs in a more advanced way by building on the foundation learned in the previous course. Come in, get experience using R and learn new ways to use the dplyr functions.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides advanced applications of the dplyr 'mutate' verb
Introduces the Rhyme Interface for hands-on experience with R and dplyr
Reinforces dplyr verb phrases for filtering, aggregating, and transforming data
Save this course
Save Build Data Analysis and Transformation Skills in R using DPLYR to your list so you can find it easily later:
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Reviews summary
Well-received course for data analysis beginners
Learners say this beginner-friendly course is excellent for helping one learn data transformation skills in R using DPLYR. Students appreciate the great instructor and fantastic material provided.
The instructor is excellent and provides fantastic material.
"Excellent instructor!"
"Great course from a great instructor."
This beginner-friendly course is a great way to learn data transformation skills in R.
"Beginner friendly, I really liked it."
"This project is very good for the beginners who want to learn data transformation using DPLYR in R."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Build Data Analysis and Transformation Skills in R using DPLYR with these
activities:
Read 'dplyr: A Grammar of Data Manipulation'
Show steps
Gain a deeper understanding of dplyr's principles and applications by reading the seminal book by the creators of dplyr.
View
Advanced R Solutions
on Amazon
Show steps
Review basic R syntax and functions
Show steps
Refresh your knowledge of fundamental R syntax and functions to strengthen your foundation for using dplyr effectively.
Browse courses on
R Programming
Show steps
-
Review basic data types, operators, and functions
-
Practice writing and executing simple R scripts
Practice DPLYR verbs
Show steps
Reinforce your understanding of dplyr verbs by practicing exercises that test your knowledge of their functionality.
Show steps
-
Review the syntax and usage of dplyr verbs
-
Complete practice exercises focused on specific dplyr verbs
-
Apply dplyr verbs to your own data sets
Three other activities
Expand to see all activities and additional details
Show all six activities
Peer discussion on dplyr use cases
Show steps
Engage with fellow learners to discuss different use cases of dplyr, exchange ideas, and gain new perspectives.
Show steps
-
Join a peer discussion group or forum
-
Participate in discussions and share your own experiences using dplyr
-
Listen attentively and engage with the insights offered by others
Create a data visualization using dplyr
Show steps
Deepen your understanding of dplyr functions by using them to create a visually engaging representation of a data set.
Show steps
-
Choose a data set and determine the insights you want to convey
-
Select appropriate dplyr functions to transform and filter the data
-
Use a data visualization tool to create a visually appealing representation of the data
Build a dplyr-based data analysis pipeline
Show steps
Apply your dplyr skills to a practical data analysis project, enhancing your ability to solve real-world problems.
Show steps
-
Define a data analysis problem and gather the necessary data
-
Design a data analysis pipeline using dplyr verbs
-
Implement the pipeline and analyze the results
Read 'dplyr: A Grammar of Data Manipulation'
Show steps
Gain a deeper understanding of dplyr's principles and applications by reading the seminal book by the creators of dplyr.
View
Advanced R Solutions
on Amazon
Show steps
Show steps
Show steps
Review basic R syntax and functions
Show steps
Refresh your knowledge of fundamental R syntax and functions to strengthen your foundation for using dplyr effectively.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Review basic data types, operators, and functions
- Practice writing and executing simple R scripts
Practice DPLYR verbs
Show steps
Reinforce your understanding of dplyr verbs by practicing exercises that test your knowledge of their functionality.
Show steps
Show steps
Show steps
- Review the syntax and usage of dplyr verbs
- Complete practice exercises focused on specific dplyr verbs
- Apply dplyr verbs to your own data sets
Three other activities
Expand to see all activities and additional details
Show all six activities
Peer discussion on dplyr use cases
Show steps
Engage with fellow learners to discuss different use cases of dplyr, exchange ideas, and gain new perspectives.
Show steps
Show steps
Show steps
- Join a peer discussion group or forum
- Participate in discussions and share your own experiences using dplyr
- Listen attentively and engage with the insights offered by others
Create a data visualization using dplyr
Show steps
Deepen your understanding of dplyr functions by using them to create a visually engaging representation of a data set.
Show steps
Show steps
Show steps
- Choose a data set and determine the insights you want to convey
- Select appropriate dplyr functions to transform and filter the data
- Use a data visualization tool to create a visually appealing representation of the data
Build a dplyr-based data analysis pipeline
Show steps
Apply your dplyr skills to a practical data analysis project, enhancing your ability to solve real-world problems.
Show steps
Show steps
Show steps
- Define a data analysis problem and gather the necessary data
- Design a data analysis pipeline using dplyr verbs
- Implement the pipeline and analyze the results
Career center
Learners who complete Build Data Analysis and Transformation Skills in R using DPLYR will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex business problems. This course may be useful for aspiring Machine Learning Engineers, as it provides a solid foundation in data analysis and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to prepare and analyze data for machine learning models.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers design and develop data visualizations to communicate insights and trends from data. This course may be useful for aspiring Data Visualization Engineers, as it provides a solid foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to prepare and transform data for effective visualization.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business processes and data analysis to identify and solve business problems. This course may be useful for aspiring Business Analysts, as it provides a strong foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to analyze and interpret data to support decision-making.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure to support data analysis and machine learning. This course may be useful for aspiring Data Engineers, as it provides a solid foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can develop the skills necessary to automate and scale data processing tasks.
Data Scientist
Data Scientist
Data Scientists leverage their expertise in machine learning, statistical modeling, and data analysis to solve complex business problems. This course may be useful for aspiring Data Scientists, as it provides a strong foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to prepare and analyze data for machine learning models.
Statistician
Statistician
Statisticians use their knowledge of statistics and data analysis to design and conduct surveys, analyze data, and interpret results. This course may be useful for aspiring Statisticians, as it provides a strong foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to clean, prepare, and analyze data for statistical analysis.
Data Analyst
Data Analyst
Data Analysts use their knowledge of data analysis and statistics to interpret data and extract meaningful insights. This course may be useful for aspiring Data Analysts, as it provides a solid foundation in data analysis using the dplyr package. By learning to use dplyr functions such as filter, aggregate, and transform, learners can develop the skills necessary to clean, manipulate, and analyze data effectively.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematical modeling and optimization techniques to improve the efficiency and effectiveness of business operations. This course may be useful for aspiring Operations Research Analysts, as it provides a solid foundation in data analysis and transformation using the dplyr package. By learning to manipulate and analyze data effectively, learners can develop the skills necessary to identify and solve operational problems.
Data Architect
Data Architect
Data Architects design and implement data architectures to meet business requirements. This course may be useful for aspiring Data Architects, as it provides a solid foundation in data modeling and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to design and implement data architectures that are efficient and scalable.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases to store and manage data. This course may be useful for aspiring Database Administrators, as it provides a solid foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to efficiently manage and query data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to assess financial risks and opportunities. This course may be useful for aspiring Quantitative Analysts, as it provides a solid foundation in data analysis and transformation using the dplyr package. By learning to manipulate and analyze financial data effectively, learners can develop the skills necessary to contribute to the development of investment strategies.
Web Developer
Web Developer
Web Developers design, develop, and maintain websites. This course may be useful for aspiring Web Developers, as it provides a solid foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to handle and process data within web applications.
Project Manager
Project Manager
Project Managers plan, execute, and oversee projects to achieve specific goals. This course may be useful for aspiring Project Managers, as it provides a solid foundation in data analysis and interpretation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to track and analyze project data to make informed decisions.
Software Developer
Software Developer
Software Developers design, develop, and maintain software applications. This course may be useful for aspiring Software Developers, as it provides a solid foundation in data manipulation and transformation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to handle and process data within software applications.
Product Manager
Product Manager
Product Managers define, prioritize, and oversee the development of products. This course may be useful for aspiring Product Managers, as it provides a solid foundation in data analysis and interpretation using the dplyr package. By learning to use dplyr verbs effectively, learners can enhance their ability to analyze and interpret data to make informed decisions about product development.
For more career information including salaries, visit:
OpenCourser.com/course/9nl4kq/build
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Build Data Analysis and Transformation Skills in R using DPLYR.
Provides a comprehensive guide to the ggplot2 package, which powerful tool for creating visualizations in R.
Save
Provides a comprehensive introduction to the R programming language, with a focus on data science applications. It covers the basics of R, as well as more advanced topics such as data manipulation, visualization, and statistical modeling.
Save
Provides a comprehensive guide to R Markdown, a powerful tool for creating dynamic and reproducible reports in R.
Provides a comprehensive introduction to machine learning in R, with a focus on practical applications.
Provides a comprehensive introduction to deep learning in R, with a focus on practical applications.
Provides a comprehensive introduction to natural language processing in R, with a focus on practical applications.
Save
Provides a comprehensive introduction to time series analysis in R, with a focus on practical applications.
Save
Provides a comprehensive introduction to spatial data analysis in R, with a focus on practical applications.
Provides a detailed guide to data manipulation in R, with a focus on the reshape2 package.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9nl4kq/build
Share
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Chris Shockley
Language
English
Good to know
Provides advanced applications of the dplyr 'mutate' verb
Introduces the Rhyme Interface for hands-on experience with R and dplyr
Reinforces dplyr verb phrases for filtering, aggregating, and transforming data
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