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Learner Reviews & Feedback for Data Analysis with R Programming by Google

4.8
stars
9,478 ratings

About the Course

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. 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, learners 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. - Understand 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....

Top reviews

RK

Feb 28, 2022

Excellent course with lucid explaination. The way instructor covers the course makes you fall in love with R. All the topics are covered beautifully. Thank coursera and Google for this awesome course.

AR

Feb 13, 2022

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!

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76 - 100 of 1,984 Reviews for Data Analysis with R Programming

By Katerina

Jul 21, 2022

My last straw was when I found the correct function for the assignment in the NEXT video, not in the one that precedes it. How did you expect me to pass it when your theory is out of order?

Moreover, this course is unnecessary for a JUNIOR Data Analyst.

By Ha N

Oct 24, 2022

why don't you teach python, it's much more popular, this course make me very dispapointed as I've encountered tremendous amount of difficulties seeking help online

Please don't waste other people's time on this course, you hurt me a lot

By Henoc S

Feb 18, 2023

Code exeuction on weekly or course challenge don't work and the question are just incoherent.

i had to use R studio download everything.

Topics are not logically orgnizated. Subjects are been repeated over and over.

By Aakash Y

Dec 27, 2021

I want to unenroll this part of my google data analytics course for now.

Took enroll option by mistake, there is no option of unenrolling coming out

Only rate course is there, please help me resolve in this issue.

By Aidan L

Feb 13, 2024

This course does not teach data analytics (how to add value with data analysis). It teaches tools used in data analytics.

By Tristan J G

Jan 18, 2023

exams with coding gets an error message everytime. waste of time

By SARASWATHI A

Aug 5, 2022

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Course challenge

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Course challenge

Graded Quiz. • 1h 5m. • 13 total points available.13 total points

DueSep 11, 11:59 PM PDT00:59:42 remainingTime remaining: 59 minutes and 42 seconds

1.

Question 1

Scenario 1, questions 1-7

As part of the data science team at Gourmet Analytics, you use data analytics to advise companies in the food industry. You clean, organize, and visualize data to arrive at insights that will benefit your clients. As a member of a collaborative team, sharing your analysis with others is an important part of your job.

Your current client is Chocolate and Tea, an up-and-coming chain of cafes.

The eatery combines an extensive menu of fine teas with chocolate bars from around the world. Their diverse selection includes everything from plantain milk chocolate, to tangerine white chocolate, to dark chocolate with pistachio and fig. The encyclopedic list of chocolate bars is the basis of Chocolate and Tea’s brand appeal. Chocolate bar sales are the main driver of revenue.

Chocolate and Tea aims to serve chocolate bars that are highly rated by professional critics. They also continually adjust the menu to make sure it reflects the global diversity of chocolate production. The management team regularly updates the chocolate bar list in order to align with the latest ratings and to ensure that the list contains bars from a variety of countries.

They’ve asked you to collect and analyze data on the latest chocolate ratings. In particular, they’d like to know which countries produce the highest-rated bars of super dark chocolate (a high percentage of cocoa). This data will help them create their next chocolate bar menu.

Your team has received a dataset that features the latest ratings for thousands of chocolates from around the world. Click hereOpens in a new tab to access the dataset. Given the data and the nature of the work you will do for your client, your team agrees to use R for this project.

Your supervisor asks you to write a short summary of the benefits of using R for the project. Which of the following benefits would you include in your summary? Select all that apply.

1 point

2.

Question 2

Scenario 1, continued

Before you begin working with your data, you need to import it and save it as a data frame. To get started, you open your RStudio workspace and load all the necessary libraries and packages. You upload a .csv file containing the data to RStudio and store it in a project folder named flavors_of_cacao.csv.

You use the read_csv() function to import the data from the .csv file. Assume that the name of the data frame is flavors_df and the .csv file is in the working directory. What code chunk lets you create the data frame?

1 point

3.

Question 3

Scenario 1, continued

Now that you’ve created a data frame, you want to find out more about how the data is organized. The data frame has hundreds of rows and lots of columns.

Assume the name of your data frame is flavors_df. What code chunk lets you review the column names in the data frame?

1 point

4.

Question 4

Scenario 1, continued

Next, you begin to clean your data. When you check out the column headings in your data frame you notice that the first column is named Company...Maker.if.known. (Note: The period after known is part of the variable name.) For the sake of clarity and consistency, you decide to rename this column Maker (without a period at the end).

Assume the first part of your code chunk is:

flavors_df %>%

What code chunk do you add to change the column name?

1 point

5.

Question 5

After previewing and cleaning your data, you determine what variables are most relevant to your analysis. Your main focus is on Rating, Cocoa.Percent, and Company. You decide to use the select() function to create a new data frame with only these three variables.

Assume the first part of your code is: 

trimmed_flavors_df <- flavors_df %>%

Add the code chunk that lets you select the three variables.

1 RunReset

What company appears in row 1 of your tibble?

1 point

6.

Question 6

Next, you select the basic statistics that can help your team better understand the ratings system in your data. 

Assume the first part of your code is:

trimmed_flavors_df %>%

You want to use the summarize() and sd() functions to find the standard deviation of the rating for your data. Add the code chunk that lets you find the standard deviation for the variable Rating.

1 RunReset

What is the standard deviation of the rating?

1 point

7.

Question 7

After completing your analysis of the rating system, you determine that any rating

By Deepan J

Aug 17, 2023

Title: Excellent Google Data Analytics Course on Coursera!

Rating: ⭐⭐⭐⭐⭐ (5/5)

I recently completed the Google Data Analytics course on Coursera, and I must say it was an outstanding experience. This course not only met my expectations but exceeded them in every aspect.

Content: ⭐⭐⭐⭐⭐

The course content is comprehensive, well-structured, and incredibly relevant. Each module was designed with clarity, providing a solid foundation before diving into more advanced topics. The real-world examples and case studies helped me understand how data analytics is applied in various industries.

Instructors: ⭐⭐⭐⭐⭐

The instructors were top-notch. They were not only knowledgeable but also had a knack for explaining complex concepts in a simple and engaging manner. Their enthusiasm and expertise kept me motivated throughout the course.

Hands-on Experience: ⭐⭐⭐⭐⭐

The hands-on assignments and projects were the highlight of the course. They allowed me to apply the concepts I learned to real datasets, giving me a taste of what it's like to work on actual data analysis projects. The step-by-step guidance and feedback provided a supportive learning environment.

Resources and Support: ⭐⭐⭐⭐⭐

The course materials, including readings, videos, and supplementary resources, were abundant and well-curated. The discussion forums were incredibly helpful, and the community aspect added a collaborative element to the learning experience. The support from both the instructors and fellow learners made problem-solving much easier.

Flexibility: ⭐⭐⭐⭐⭐

As a Coursera course, the flexibility it offered was invaluable. I could learn at my own pace, which was perfect for balancing with my other commitments. The modular structure also allowed me to revisit specific sections when needed.

Certification: ⭐⭐⭐⭐⭐

The course completion certificate holds genuine value. It serves as a testament to the skills I've acquired and has already proven to be a valuable addition to my professional profile.

Overall, I can confidently say that the Google Data Analytics course on Coursera is a must-take for anyone interested in entering the field of data analytics or looking to enhance their existing skills. The depth of knowledge, quality of instruction, and practical experience provided are truly exceptional. I'm grateful for this learning opportunity and can't wait to explore more courses in this domain.

By Rathan G

Apr 12, 2023

The course is designed to introduce learners to the basics of R programming language and its application in data analytics. The course covers various topics such as data cleaning, data visualization, data manipulation, and data analysis. The course provides a mix of video lectures, interactive quizzes, and hands-on exercises that help learners to understand the concepts better.

The course starts with an introduction to R programming language, and gradually progresses to more advanced topics such as data visualization using ggplot2, data manipulation using dplyr, and statistical analysis using inferential statistics. The course also includes several case studies and examples that help learners to apply the concepts in real-world scenarios.

One of the main advantages of this course is that it is offered by Google, which is a reputable organization in the field of technology. The course is designed to be self-paced, which means learners can complete the course at their own pace and convenience. The course also includes a dedicated discussion forum where learners can ask questions and get help from the community.

Overall, the Data Analytics in R Language course by Google is a well-structured and comprehensive course that provides learners with a solid foundation in R programming and its application in data analytics. The course is suitable for beginners as well as experienced professionals who want to enhance their skills in data analytics using R.

By Raphaella K G

Oct 14, 2023

This must be one of the most challenging courses I've taken in this program! Not only was I a total newbie to programming languages, but I also had to rethink the way I look at data analytics as well. I always thought that data analysis only involved processing, cleaning, and analyzing the data, it never occurred to me that programming languages are involved as well. Even though it was really challenging, I really had fun learning to code, especially when it already got to coding my data viz. I realized that there are completely different tools analysts can use to achieve the same results. I am now more open and excited to learn other tools for analysis well beyond this program. The way this course was structured really helped a lot! It helped me ease into the new language, get to know it, and practice it with the activities. The hands-on activities are what I appreciate the most, not only did they guide me to what I needed to accomplish for that activity, but they also allowed me to use different functions and find out techniques I could use to make the code or my analysis more efficient. Thank you so much for your hard work!

By Josh W

Oct 23, 2022

The main female instructor was fantastic. The tools taught outstanding. However, there are two parts that need a review. The first is the idea that hiring managers prefer candidates who challenge the corporate status quo with new ideas. That may be soley with Google as I have yet to meet one in the general private sector who did. Most intereviewers are solely interested in what the candidate can produce for the firm at the time. New ideas are not part of the picture until the ones immediately pressing on the firm are resolved. The second issue was with your 'bias' button as it relates to statistical analysis. That error becamse the source of my capstone project. You have confused bias for sampling error. A store manager misjudging which film will sell well and over-ordering the wrong tapes is not a bias error but a sampling error. It is the equivalent of saying that your car has a bias for steering left due to an underinflated tire. That is a lean, not a bias.

That said. my capstone project describes real bias that has been going on in the country for decades.

By Atul G

May 30, 2022

This course looks at how to use programming in R to perform all of the stages in the data analysis process, from preparing and processing data, to performing preliminary and advanced analysis, to finally sharing the findings with your audience. The steps are very clearly shown with the trainer guiding you at the right pace. There are plenty of opportunities to follow along as instructed and understand the techniques by doing them - this is a great way to learn how to code. Various resources are linked to at key stages allowing for further reading on core concepts and even keeping 'cheatsheets' on key R packages for future reference. The priniciple of ongoing learning is conveyed perfectly with the instructor acknowledging her own meandering journey as an analyst and as a coder. Finally, the use of R markdown to display the steps you've used in your analysis and to easily produce a final report or presentation is extremely valuable for me. I will definitely be going through this course several times as I practice using R now and in the future. Excellent course 10/10

By Rick

Jun 4, 2022

Excellent base knowledge for R programming aimed at data analysis delivered in an easy to follow manner and at a reasonable cost. The course not only gives the student a good start but also provides lots of accessible resources and tips to move from a novice R programmer towards mastery. Remarkably, everything worked, I write this because I have attempted to follow instructions for such things as downloading programming ide's in other online courses and found them outdated, not so here. Everything is current and up to date. I think any student with average grades in the past can work through this course, perhaps repeating sections at times, and find themselves fairly R proficient in a timely manner. Personally with two hours effort every morning while my pre-schooler was still asleep I was confidently coding in less than a month (while using an old outdated Chromebook I bought for $100, not necessary to invest thousands in a new computer).

By Noah O

Mar 19, 2023

I highly recommend Google's Data Analysis with R Programming course as an introduction to R. The course quickly gets one up and running quickly. I was able to install R and R Studio/Posit, learn how to navigate R Studio, install and load packages, and use R to clean, analyze, visualize, and share data analyses. I think this course would be great for an aspiring analyst with little to no experience or someone like me who is an experienced analyst wanting to learn R. You will get out of the course what you put into it. It's possible to get a rudimentary understanding of R by quickly completing only the required elements, but one thing that I appreciated is that the course points at a number of resources for further inquiry and study. You won't leave this 5 week course an expert, but there is plenty here to launch one successfully. I'm impressed with how much I learned over the 5 weeks.

By A.barani

Nov 27, 2022

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By Kelum B

Sep 5, 2022

This is the first time I followed a course from google & coursera. This is a most valueble course for the persons who wish to enter the data analyst career. The course content is much clear and the lecturer also explains each theorytical and practical parts clearly in a way that any one including the persons who don't have much listening skills, can understand.It is beacause the pronounciation is that much clear.

On the other hand, the quizes and lessons have been arranged in a proper sequence. Each reading supports with clear theories and relevant codes as well as other useful website links. There is a seperate glossary for each part as well. Course covers entire process of the data analysis with practical examples and more.

Finally course is great and thank you very much for the google and coursera team.

Kelum (Sri Lanka)

By Samaila B

Jul 11, 2023

I thoroughly enjoyed the Data Analysis with R Programming by Google course. It provided a comprehensive and well-structured introduction to data analysis using R. The course content was informative, covering essential topics such as data manipulation, visualization, and statistical analysis. The hands-on exercises and assignments helped solidify my understanding of the concepts and allowed me to apply them to real-world datasets. The course instructor was knowledgeable and engaging, and the interactive learning environment made it easy to follow along and ask questions. Overall, the course was a valuable learning experience that equipped me with the skills and confidence to perform data analysis using R. I highly recommend it to anyone interested in enhancing their data analysis capabilities with R programming.

By Yunfang W

Feb 2, 2024

After completing this course, I want to express my gratitude to the instructor, Carrie. I appreciate her effective teaching style, characterized by a well-balanced speaking speed that is neither too fast nor too slow. This is particularly beneficial for those of us using English as a second language. Carrie's clear and standard pronunciation enhances my understanding of the course content. She has been instrumental in guiding me through the material, making the learning experience enjoyable. Surprisingly, I found myself developing an interest in programming, despite having no prior knowledge of computer programming. Carrie's expertise and teaching approach have made a significant impact on my learning journey.

By Aung K L

Dec 27, 2023

R is a powerful and widely-used programming language for statistical computing and data analysis. Its strengths lie in its specialized tools for statistical modeling, comprehensive visualization libraries like ggplot2, and an active community that contributes to a vast repository of packages. While it may have a steeper learning curve for beginners, its focus on reproducibility through tools like R Markdown and its open-source nature make it an attractive choice for researchers and data analysts. Despite potential concerns about speed and syntax complexity, R remains a valuable tool for those seeking in-depth statistical analysis and visualization capabilities in their data projects.

By Gabriel d C G S

Jan 18, 2024

Eu simplesmente amei esse curso. Isto envolve aspectos da didática da professora e os materiais. Eu sou grato ao Google por disponibilizar esses conhecimentos valiosos de programação básica e análise de dados em um preço que cabe no bolso( affordable).Assim, eu estou muito contente pela oportunidade de ser ter aulas EAD dessa maravilhosa empresa de tecnologia mundial. I simply loved this course. This involves aspects of the teacher's teaching and materials. I'm grateful to Google for making this valuable knowledge of basic programming and data analysis available at an affordable price. Thus,I am so glad for this oportunity of being a pupil of this wonderful global tech company.

By Cat V H

Jun 11, 2022

Thanks Carrie, the instructor of this course, along with Google and Coursera, to offer this course here. I learnt so much about programming with R, and I really enjoyed seeing how my code came to work in the RStudio console. There are stilll many things to learn about R, but this course guided me where to look for resources to learn and practice more. In this course, I learnt all about the analysis tasks with R coding, like cleaning, organizing, transforming, visualizing , reporting, and documenting data. Thanks again, it's great to see how far I've reached in this Google Certificate track. Google and Coursera, please keep up your good work!

By Yahya M A S

Sep 12, 2022

This course was amazing since it explain R to me in an easy way, I don't know anything about R before. This course gives me a good starting and builds a foundation for my subsequent R learning and certification in data analysis using R. The learning process flow was excellent, it picked up what you need without digging deep into the language, and it was a great strategy, by the way, since we share our findings through Tableau, I think if the course was included how we can integrate the power of data analysis and visualization of R within the power of Tableau, so I think this will be useful.

Thanks Google for this wonderful trainning cource

By Tracey

Jan 16, 2022

I absolutely love the diversity in the presenters for each of these courses in the program. The presenters were very knowledgeable but were excellent in breaking down the information in a beginner-friendly manner. There was so much content, but possible to learn and understand. I really loved the interactive lessons that gave the learner the plenty opportunity to practice the new content within each lesson. I really enjoyed this program that helped me to learn what I needed to learn without feeling overwhelmed. It was also extremely helpful that the design of the new information was always presented in a manner that real-world applications.

By MOHD D

Apr 9, 2023

After putting in a lot of hard work, I'm excited to say that I have achieved my goal of becoming a data analyst."

This is one of the best courses, thank you for everything

"I was thoroughly impressed by the 'Data Analysis with R Programming' course on Coursera. The course covered a wide range of topics in data analysis, from data manipulation to statistical modeling, and provided hands-on experience working with real-world datasets. I found the course to be engaging and comprehensive, and would highly recommend it to anyone looking to build a strong foundation in data analysis and programming."

By Daigo T

Jul 11, 2022

I recommend this course. This was the best course for me to learn R basics. I had zero knowledge before taking this course. After completing this course, I felt confident carrying out basic data analysis processes (e.g. data clearning, data analysis with graphs and charts, visualization functions). Thank you so much Google team for designing this wonderful course. I am happy that I had started leraning about R with this Google course. All the course contents were made "digestable" for somebody like me. The course instructor was also encouraging thorughout the course. Many thanks :)