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Build Data Analysis and Transformation Skills in R using DPLYR

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.

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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)

Enroll now

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

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

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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

Coming soon We're preparing activities for Build Data Analysis and Transformation Skills in R using DPLYR. These are activities you can do either before, during, or after a course.

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 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 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 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 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 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
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 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 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 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 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 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 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 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 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 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.

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 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.
Provides a comprehensive guide to R Markdown, a powerful tool for creating dynamic and reproducible reports in R.
Provides a comprehensive introduction to natural language processing in R, with a focus on practical applications.
Provides a comprehensive introduction to time series analysis in R, with a focus on practical applications.
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.

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