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Build Data Analysis tools using R and DPLYR

In this 2-hour long project-based course, you will learn one of the most powerful data analysis tools of the experts: the DPLYR package. By learning the six main verbs of the package (filter, select, group by, summarize, mutate, and arrange), you will have the knowledge and tools to complete your next data analysis project or data transformation.

By the end of this project, you will be able to:

Use the six main dplyr verbs

Understand the dplyr package and its capabilities

Get hands-on practice using R and dplyr functions

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, this means instant access to a cloud desktop with R and the appropriate packages installed.

Notes:

- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.

- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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What's inside

Syllabus

Intro to dplyr

Welcome to the first module! In this module, 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 the dplyr verbs through hands on exercises. Come in and get experience using R and the dplyr functions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Emphasizes dplyr, which is a cornerstone tool utilized by data analysts

Provides practical R and dplyr function implementation

Designed for an immersive, hands-on learning experience through Rhyme

Access to pre-configured cloud desktops simplifies the learning environment

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Save Build Data Analysis tools using R and DPLYR to your list so you can find it easily later:

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Reviews summary

Well received beginners guide to dplyr

Learners say this beginner-level course is useful for those who want to learn more about using DPLYR with R for data analysis. Many students say the lectures are well explained and easy to follow, making it a great choice for those who are new to the subject.

Nicely structured for beginners.

"nicely structured for beginner.i liked it."

"Great guided project. Pretty much explained"

"It is a great learning course for a beginner."

Well taught and easy to understand.

"Well summarized and articulated."

"Really mindful and easy to learn!"

"Very explanatory and well taught."

Good intro course for DPLYR.

"Nice for revision"

"Nice course for beginners."

"A good introduction to dplyr."

Platform for this course can be problematic.

"The platform for this course is really cumbersome and distracting."

"Course is very nice and crisp. Only problem was the Rhyme server used for practice. Faced lots of issues."

Very basic with limited learning outcome.

"Very basic, very short. Near zero learning outcome."

"Nice intro, wished there was more complex examples"

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 tools using R and DPLYR with these activities:

Review Data Science with R Book

Show steps

Review the Data Science with R book to strengthen your understanding of the dplyr package and its functions.

View R for Data Science: Import, Tidy, Transform,... on Amazon

Show steps

Follow Tutorials on dplyr

Show steps

Explore tutorials on dplyr to expand your knowledge and discover advanced techniques.

Browse courses on Dplyr Package

Show steps

Search for online tutorials
Follow the steps and try out the examples

Join a Study Group on dplyr

Show steps

Collaborate with peers in a study group to discuss concepts, share insights, and learn from each other.

Browse courses on Dplyr Package

Show steps

Find or create a study group
Establish a regular meeting schedule
Take turns presenting and discussing topics

Five other activities

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Show all eight activities

Solve Practice Exercises on dplyr

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Engage in practice drills on dplyr to reinforce your understanding of its syntax and functionality.

Browse courses on Dplyr Package

Show steps

Find online exercises or use the resources provided in the course
Solve the exercises
Review your answers

Compile a Resource List on dplyr

Show steps

Create a comprehensive list of resources on dplyr, including tutorials, documentation, and examples.

Browse courses on Dplyr Package

Show steps

Search for resources online
Categorize and organize the resources
Share the list with others

Create a Project using dplyr Functions

Show steps

Develop a project that utilizes dplyr functions to enhance your proficiency in data manipulation and analysis.

Browse courses on Dplyr Package

Show steps

Identify a suitable dataset
Load the dataset into R
Apply dplyr functions to explore and transform the data
Summarize and visualize the results

Participate in a Data Science Competition

Show steps

Challenge yourself in a data science competition to test your skills and gain practical experience.

Browse courses on Dplyr Package

Show steps

Find an appropriate competition
Download the dataset
Develop a solution using dplyr functions
Submit your solution

Mentor a Beginner on dplyr

Show steps

Share your knowledge by mentoring a beginner and guiding them through the concepts of dplyr.

Browse courses on Dplyr Package

Show steps

Find a beginner to mentor
Establish a regular communication schedule
Provide guidance and support

Career center

Learners who complete Build Data Analysis tools using R and DPLYR will develop knowledge and skills that may be useful to these careers:

Financial Analyst

Financial Analysts use financial data to make recommendations on investments and financial decisions. R and DPLYR are commonly used by Financial Analysts to analyze financial data, and this course would be particularly helpful to someone entering this field since it provides a hands-on approach to using both of these tools. The six main verbs taught in this course: filter, select, group by, summarize, mutate, and arrange are all essential to the work done by a financial analyst.

See salaries and explore the career path for Financial Analyst

Data Scientist

Data Scientists combine programming and analytical skills to extract insights from data, and this course would aid an individual who wants to become a Data Scientist by teaching them some of the tools and techniques used by those in the field. R and DPLYR are among the most commonly used tools by Data Scientists, and the six verbs taught in this course are essential to the work done by a Data Scientist.

See salaries and explore the career path for Data Scientist

Investment Analyst

Investment Analysts evaluate potential investments, make investment recommendations, and manage investment portfolios. R and DPLYR are commonly used by Investment Analysts to analyze investment data, and this course would be particularly helpful to someone entering this field since it provides a hands-on approach to using both of these tools. The six main verbs taught in this course: filter, select, group by, summarize, mutate, and arrange are all essential to the work done by an investment analyst.

See salaries and explore the career path for Investment Analyst

Risk Analyst

Risk Analysts identify, assess, and manage risks. R and DPLYR are commonly used by Risk Analysts to analyze risk data, and this course would be particularly helpful to someone entering this field since it provides a hands-on approach to using both of these tools. The six main verbs taught in this course: filter, select, group by, summarize, mutate, and arrange are all essential to the work done by a Risk Analyst.

See salaries and explore the career path for Risk Analyst

Quantitative Analyst

Quantitative Analysts apply statistical and mathematical models and techniques to data to evaluate potential investment strategies and developments. The knowledge of R and DPLYR that this course provides may help build a foundation for becoming a Quantitative Analyst, as these tools can be used to make basic and high-level calculations that are often the first step taken by a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Statistician

Statisticians collect, analyze, interpret, and present data, working in a wide range of industries like insurance, finance, market research, public policy, and health care. This course would be helpful for a student aspiring to become a Statistician since it teaches R and DPLYR, two tools commonly used by those in this field. The six verbs taught in this course are particularly relevant to the role, as they are used by Statisticians to organize their data in a way that makes performing statistical analysis more accessible and efficient.

See salaries and explore the career path for Statistician

Epidemiologist

Epidemiologists investigate the occurrence of diseases and other health problems in populations. They use a variety of tools to analyze data, including R and DPLYR. This course could be a great stepping stone for someone looking to become an Epidemiologist, as it would provide a foundation in using both of these tools. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience in using R and DPLYR.

See salaries and explore the career path for Epidemiologist

Biostatistician

Biostatisticians apply statistics to biological or medical data to solve scientific questions and to develop and evaluate health-related products and services. R and DPLYR are commonly used by Biostatisticians to analyze their data, and this course would be particularly helpful to someone entering this field since it provides a hands-on approach to using these two tools. The six main verbs taught in this course are often the first steps taken by a Biostatistician.

See salaries and explore the career path for Biostatistician

Business Analyst

Business Analysts analyze business data to identify opportunities for improvement. This course could be helpful for someone who wants to become a Business Analyst, as it would help them learn how to use R and DPLYR, two tools commonly used by Business Analysts. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience using these tools.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers gather and analyze data about markets, products, and customers. This course could be useful for someone who wants to become a Market Researcher, as it would help teach them how to use R and DPLYR, two tools commonly used to analyze market data. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience using these tools.

See salaries and explore the career path for Market Researcher

Data Analyst

Data Analysts collect data from a wide variety of sources and formats, and convert it into a form that can be analyzed by other members of the team. This course would help someone become a Data Analyst by teaching how to use R and DPLYR to sort, filter, and perform rudimentary analysis on data, which is nearly always the first step taken by a Data Analyst. The six verbs taught by this course: filter, select, group by, summarize, mutate, and arrange are all essential to this first step in data analysis.

See salaries and explore the career path for Data Analyst

Database Administrator

Database Administrators design, implement, and maintain databases. This course would provide a foundation for someone who wants to become a Database Administrator, as it would teach them how to use R and DPLYR, two programming languages commonly used by Database Administrators. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience using these languages.

See salaries and explore the career path for Database Administrator

Data Engineer

Data Engineers design, build, and maintain the infrastructure that stores and processes data. This course would be useful for someone who wants to become a Data Engineer, as it would help teach them how to use R and DPLYR, two tools commonly used by Data Engineers. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience using these tools.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software applications. This course would provide a foundation for someone who wants to become a Software Engineer, as it would teach them how to use R and DPLYR, two programming languages commonly used by Software Engineers. Additionally, the course's focus on hands-on learning would be beneficial for someone who wants to gain practical experience using these languages.

See salaries and explore the career path for Software Engineer

Project Manager

Project Managers plan, execute, and close projects. This course would provide a basic introduction to R and DPLYR, which Project Managers can use to analyze data and make better decisions. Additionally, the course may help build a foundation for a Project Manager who wishes to learn more advanced data analysis techniques in the future.

See salaries and explore the career path for Project Manager

Reading list

We've selected 15 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 tools using R and DPLYR.

R Programming for Data Science

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Provides a comprehensive introduction to the R programming language and its use in data science. It covers a wide range of topics, from data manipulation and visualization to statistical modeling and machine learning. This book valuable resource for anyone who wants to learn more about R and its applications.

Build Data Analysis tools using R and DPLYR

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Well received beginners guide to dplyr

Activities

Career center

Reading list

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