Data Analysis with R Programming
This course is the seventh course in the Google Data Analytics Certificate. In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways.
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- Level Foundation
- المدة 37 ساعات hours
- الطبع بواسطة Google
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Offered by
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This course is the seventh course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you'll learn about the programming language known as R. You'll find out how to use RStudio, the environment that allows you to work with R. This course will also cover the software applications and tools that are unique to R, such as R packages. You'll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Examine the benefits of using the R programming language. - Discover how to use RStudio to apply R to your analysis. - Explore the fundamental concepts associated with programming in R. - Explore the contents and components of R packages including the Tidyverse package. - Gain an understanding of dataframes and their use in R. - Discover the options for generating visualizations in R. - Learn about R Markdown for documenting R programming.الوحدات
The exciting world of programming
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3
Videos
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4
Readings
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1
Plugin
3
Videos
- Introduction to the exciting world of programming
- Fun with R
- Carrie: Getting started with R
4
Readings
- Course syllabus
- Helpful resources and tips
- The R-versus-Python debate
- Learning Log: Get ready to explore R
Programming as a data analyst
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2
Videos
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2
Readings
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3
Quiz
2
Videos
- Programming languages
- Introduction to R
2
Readings
- Ways to learn about programming
- From spreadsheets to SQL to R
3
Quiz
- Optional Hands-On Activity: Downloading and installing R
- Optional Hands-On Activity: R Console
- Test your knowledge on programming languages
Learn programming using RStudio
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1
Videos
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2
Readings
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3
Quiz
1
Videos
- Intro to RStudio
2
Readings
- When to use RStudio
- Connecting with other analysts in the R community
3
Quiz
- Hands-On Activity: Cloud access to RStudio
- Optional Hands-On Activity: Get started in RStudio Desktop
- Test your knowledge on programming with RStudio
Module 1 challenge
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1
Readings
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1
Quiz
1
Readings
- Glossary: Terms and definitions
1
Quiz
- Module 1 challenge
Understand basic programming concepts
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2
Videos
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3
Readings
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1
Quiz
2
Videos
- Programming using RStudio
- Programming fundamentals
3
Readings
- Vectors and lists in R
- Dates and times in R
- Other common data structures
1
Quiz
- Test your knowledge on programming concepts
Explore coding in R
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1
Videos
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2
Readings
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2
Quiz
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1
Plugin
1
Videos
- Operators and calculations
2
Readings
- Logical operators and conditional statements
- Guide: Keeping your code readable
2
Quiz
- Hands-On Activity: R sandbox
- Test your knowledge on coding in R
Learning about R packages
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2
Videos
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1
Readings
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2
Quiz
2
Videos
- The gift that keeps on giving
- Welcome to the tidyverse
1
Readings
- Available R packages
2
Quiz
- Hands-On Activity: Installing and loading tidyverse
- Test your knowledge on R packages
Explore the tidyverse
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3
Videos
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1
Readings
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1
Quiz
3
Videos
- More on the tidyverse
- Use pipes to nest code
- Connor: Coding tips
1
Readings
- R resources for more help
1
Quiz
- Test your knowledge on the tidyverse
Module 2 challenge
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1
Readings
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1
Quiz
1
Readings
- Glossary: Terms and definitions
1
Quiz
- Module 2 challenge
Explore data and R
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3
Videos
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2
Readings
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2
Quiz
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1
Assignment
1
Assignment
- Hands-on Activity: Create your own data frame
3
Videos
- Data in R
- R data frames
- Working with data frames
2
Readings
- More about tibbles
- Data-import basics
2
Quiz
- Hands-On Activity: Importing and working with data
- Test your knowledge on R data frames
Cleaning data
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3
Videos
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4
Readings
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2
Quiz
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1
Plugin
3
Videos
- Cleaning up with the basics
- Organize your data
- Transforming data
4
Readings
- File-naming conventions
- More on R operators
- Optional: Manually create a data frame
- Wide to long with tidyr
2
Quiz
- Hands-On Activity: Cleaning data in R
- Test your knowledge on cleaning data
Take a closer look at the data
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2
Videos
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1
Readings
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2
Quiz
2
Videos
- Same data, different outcome
- The bias function
1
Readings
- Working with biased data
2
Quiz
- Hands-On Activity: Changing your data
- Test your knowledge on R functions
Module 3 challenge
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1
Readings
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1
Quiz
1
Readings
- Glossary: Terms and definitions
1
Quiz
- Module 3 challenge
Create data visualizations in R
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4
Videos
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1
Readings
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3
Quiz
4
Videos
- Visualizations in R
- Visualization basics in R and tidyverse
- Getting started with ggplot()
- Joseph: Career path to people analytics
1
Readings
- Common problems when visualizing in R
3
Quiz
- Hands-On Activity: Visualizing data with ggplot2
- Hands-On Activity: Using ggplot
- Test your knowledge on data visualizations in R
Explore aesthetics in analysis
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3
Videos
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3
Readings
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3
Quiz
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1
Plugin
3
Videos
- Enhancing visualizations in R
- Doing more with ggplot
- Aesthetics and facets
3
Readings
- Aesthetic attributes
- Smoothing
- Filtering and plots
3
Quiz
- Hands-On Activity: Aesthetics and visualizations
- Hands-On Activity: Filters and plots
- Test your knowledge on aesthetics in analysis
Annotate and save visualizations
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2
Videos
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2
Readings
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2
Quiz
2
Videos
- Annotation layer
- Saving your visualizations
2
Readings
- Adding annotations in R
- Saving images without ggsave()
2
Quiz
- Hands-On Activity: Annotating and saving visualizations
- Test your knowledge on annotating and saving visualizations
Module 4 challenge
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1
Readings
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1
Quiz
1
Readings
- Glossary: Terms and definitions
1
Quiz
- Module 4 challenge
Develop documentation and reports in RStudio
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3
Videos
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2
Readings
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2
Quiz
3
Videos
- Documentation and reports
- Overview of R Markdown
- Using R Markdown in RStudio
2
Readings
- R Markdown resources
- Optional: Jupyter notebooks
2
Quiz
- Hands-On Activity: Your R Markdown notebook
- Test your knowledge about documentation and reports
Create R Markdown documents
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3
Videos
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1
Quiz
3
Videos
- Structure of markdown documents
- Meg: Programming is empowering
- Even more document elements
1
Quiz
- Test your knowledge about creating R Markdown documents
Understand code chunks and exports
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2
Videos
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1
Readings
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3
Quiz
2
Videos
- Code chunks
- Exporting documentation
1
Readings
- Output formats in R Markdown
3
Quiz
- Hands-On Activity: Adding code chunks to R Markdown notebooks
- Hands-On Activity: Exporting your R Markdown notebook
- Test your knowledge on code chunks
Module 5 challenge
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1
Readings
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1
Quiz
1
Readings
- Glossary: Terms and definitions
1
Quiz
- Module 5 challenge
Course wrap-up
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2
Readings
2
Readings
- Reflect and connect with peers
- Coming up next...
Auto Summary
Explore the foundational aspects of data analysis with "Data Analysis with R Programming." This course, part of the Google Data Analytics Certificate, focuses on mastering R and RStudio for cleaning, organizing, analyzing, visualizing, and reporting data. Taught by Google data analysts, it covers R packages, dataframes, and visualization techniques, and is ideal for beginners aiming for entry-level data analyst roles. Available on Coursera with various subscription options, the course spans 2220 minutes.
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