Data Analysis with R Programming
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 …
Data Analysis with R Programming
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.
Describe the R programming language and its programming environment
Explain the fundamental concepts associated with programming in R including functions, variables, data types, pipes, and vectors
Describe the options for generating visualizations in R
Demonstrate an understanding of the basic formatting R Markdown to create structure and emphasize content
Syllabus
Syllabus - What you will learn from this course
Week 1
Programming and data analytics
Week 2
Programming using RStudio
Week 3
Working with data in R
Week 4
More about visualizations, aesthetics, and annotations
Week 5
Documentation and reports
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is data analytics?
Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. We use and create data everyday, like when we stream a show or song or post on social media.
Data analytics is the collection, transformation, and organization of these facts to draw conclusions, make predictions, and drive informed decision-making.
Why start a career in data analytics?
The amount of data created each day is tremendous. Any time you use your phone, look up something online, stream music, shop with a credit card, post on social media, or use GPS to map a route, you’re creating data. Companies must continually adjust their products, services, tools, and business strategies to meet consumer demand and react to emerging trends. Because of this, data analyst roles are in demand and competitively paid.
Data analysts make sense of data and numbers to help organizations make better business decisions. They prepare, process, analyze, and visualize data, discovering patterns and trends and answering key questions along the way. Their work empowers their wider team to make better business decisions.
Why enroll in the Google Data Analytics Certificate?
You will learn the skill set required for becoming a junior or associate data analyst in the Google Data Analytics Certificate. Data analysts know how to ask the right question; prepare, process, and analyze data for key insights; effectively share their findings with stakeholders; and provide data-driven recommendations for thoughtful action.
You’ll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week. Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You’ll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set.
After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data analytics.
What background is required?
No prior experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.
Do you need to be strong at math to succeed in this certificate?
You don't need to be a math all-star to succeed in this certificate. You need to be curious and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math, it's about asking the right questions, finding the best sources to answer your questions effectively, and illustrating your findings clearly in visualizations.
What tools and platforms are taught in the curriculum?
You'll learn to use analysis tools and platforms such as spreadsheets (Google Sheets or Microsoft Excel), SQL, presentation tools (Powerpoint or Google Slides), Tableau, RStudio, and Kaggle.
Will you be teaching R or Python?
This program teaches the open-source programming language, R. R is a great starting point for foundational data analysis, and offers helpful packages for beginners to apply to their projects. We do not cover Python in the curriculum but encourage you to explore Python after completion if you'd like to continue your learning journey.
Which “spreadsheet” platform is being taught?
Learners can self-select which platform they want to use throughout the program: Google Sheets or Microsoft Excel. It’s up to the learner’s preference, and all activities throughout the syllabus can be performed on either platform.
Do you need to take each course in course order?
We highly recommend completing the courses in the order presented because the content in each course builds on information from earlier lessons.
Reviews
Carrie's enthusiam for R was contagious. She provides clear and easy to understand explanations, and she is pleasant to listen to. It was easy to follow up. I am myself an R enthusiast now. Thank you!
Tough stuff! Trying to remember the correct syntax for filtering was stressful but I'm so grateful to learn R. Thank you for this introduction. The videos were good but the hands-on really helped me.
The analytics with R is used for analysis in easy manner and its also used for creating and visuliazation the data an analysist easily given a accurate results in make decision making Thankyou
The course was detailed and the instructor was the best by far. She explained a lot of concepts well and the hands-on activities got me interested in learning even more of R. Thanks Carrie!
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