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Learner Reviews & Feedback for Go Beyond the Numbers: Translate Data into Insights by Google

4.8
stars
498 ratings

About the Course

This is the third of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll learn how to find the story within data and tell that story in a compelling way. You'll discover how data professionals use storytelling to better understand their data and communicate key insights to teammates and stakeholders. You'll also practice exploratory data analysis and learn how to create effective data visualizations. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you build your data analytics skills to prepare for your career. Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Use Python tools to examine raw data structure and format -Select relevant Python libraries to clean raw data -Demonstrate how to transform categorical data into numerical data with Python -Utilize input validation skills to validate a dataset with Python -Identify techniques for creating accessible data visualizations with Tableau -Determine decisions about missing data and outliers -Structure and organize data by manipulating date strings...

Top reviews

JM

Aug 22, 2023

Very Helpful Course! The storytell methods described are really helpful to me. I have always had an issue with getting my point across but now I know where my problem was and have corrected it.

RR

Sep 15, 2023

I really enjoyed this and look forward to going deeper into this. This course touched the basics...but they touched the right basics and have made me WANT to do more on my own.

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1 - 25 of 79 Reviews for Go Beyond the Numbers: Translate Data into Insights

By Amos J H

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Jun 7, 2023

This is the most poorly designed and delivered course I've taken on Coursera. The instructor seems to be reading a script in which he's constantly emphasizing the wrong word. The labs are disorganized and the tasks don't match the learning objectives. I'm feeling much more confused at the end of this course than I was at the beginning.

By Vishal P

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May 28, 2023

This course is for beginners in Data Analytics domain, Intermediate and above canditates please dont spend your time on this course, you will come across same terms , that you have already learned, namely EDA, Pandas, Basic Tableau

By S M G A N

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Jul 10, 2023

I just finished the third course of the Google Advanced Data Analytics Certificate, "Go Beyond the Numbers: Translate Data into Insights." This training taught me to use Python and Tableau to study raw data, uncover trends, and convey results to stakeholders. The training was quite instructive and well-structured. The instructor did an excellent job of getting the principles straightforwardly and succinctly. The hands-on exercises also helped to reinforce the information. The abilities I gained in this course will be helpful in my future profession. I am now more prepared to utilize data to tell stories and share insights with others. I am also more confident in examining and analyzing data using Python and Tableau. Overall, I advise anyone interested in learning more about data analytics to take this course. It is an invaluable resource for anybody looking to advance their knowledge in this profession. Here are some examples of how the skills I learned in this course can benefit me in the future: I will be able to analyze data and detect trends using Python and Tableau. I will clearly and concisely explain data results to stakeholders. I will be able to convey stories with statistics and influence decision-making. These abilities will help me develop in my data analytics job.

By Caro C

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Oct 24, 2023

Out of all the modules in the Google Advanced Data Analytics Course, this is my favorite one. The instructor is very passionate about what he is teaching and the way he explains the Pandas concepts in Python by dividing it to different sections is fantastic. I also love the Tableau class, it's very insightful that we learn about how to make stories and dashboard. I definitely appreciate the knowledge. One of the best courses out there

By BELGACEM G

•

Jun 15, 2023

je remerci toutes l'equipe , vous etes formidables

By Islands

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Dec 30, 2023

Although I have not completed this course by now and am halfway done, I feel extremely disappointed with this advanced course. In this advanced course, course 1 is the intro, and courses 2 and 3 discuss fundamental Python analysis and visualization using numpy, pandas, matplotlib, and seaborn. By viewing content, courses 4 - 6 are advanced Python analysis, such as Introduction to Machine Learning and Regression Analysis. Let's start talking about courses 2 and 3. They throw you everything, and you must figure it out alone. It's just like you haven't learned Allegra yet, and they throw you calculus staff. How can you learn how to run if you don't know how to walk? It feels like impossible. If you have no previous Python experience, don't take this course! It will keep and keep confusing you. Let's have an example by looking at course content. In course 3, they taught you data analysis, visualization, and data cleaning afterward. This does not make any sense. If you aren't familiar with data analysis yet, data analysis should follow the steps in order(the steps might differ, but the structure is the same): Ask questions, data collect, data clean, analyze, and visualize. They don't teach in order, which is ridiculous, in my opinion. I learned content similar to this course about two years ago and recently re-picked it up for review. But for sure, if you have yet to gain experience with Python, don't take this course; find something better, I promise. At least, it confused me more.

By Austin K

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Jul 31, 2023

This course seems to have been thrown together in a hurry. The course isn't structured very well. Many inaccuracies in the assignments and sample answers. An instructor who looks like he just got out of bed.

Many of the instructors seem to have been thought by the same public speaking instructor. People want to learn data analytics, not look at some instructor who is waving their hands all over the place. People who are good at their jobs don't always make good instructors.

I believe it would be much better to sign up for a Coursera offering by an accredited college where the instructors have a better understanding of how to teach.

By John E

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Apr 25, 2023

The materials and presentations are excellent, but I am not a fan of the busy work involved in the end of course PACE portfolio work. Professional presentation is certainly important, but you end up diluting the course by including so much of this material. Furthermore, having worked on many projects, I can tell you that the workflow process is so iterative that trying to "shoe horn" the process into a four letter acronym -- which is better than the six letter acronym in the previous specialization -- is both reductionistic and frankly artificial. My suggestions are as follows: remove this excess material and "re-factor" the PACE/portfolio material into one course, perhaps the capstone course. Otherwise, I learned quite a bit.

By Saeed V

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Dec 19, 2023

Course 3, 'Go Beyond the Numbers: Translate Data into Insights,' in the Advanced Data Analytics specialization by Google on Coursera has been an enriching experience. I chose this course to enhance my ability to translate data into actionable insights, and it has significantly helped me achieve that goal. The practical approach to finding and sharing stories using data, exploring and cleaning raw data, and creating impactful data visualizations and presentations has been invaluable. I particularly loved the real-world applications of the course content, which helped me a lot.

By Himansu H D

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Mar 14, 2024

This course was very helpful and provided great insights on how to clean data, how to use Python libraries as well Tableau Public Software tool to visualize data, and how to present data using PACE workflow. I learned more and in great depth about six steps of exploratory data analysis. All instructors in this course did great job explaining course materials in clear and concise manner. Thank you also to Coursera for hosting this course on your platform and to Google for creating such important course.

By Siva S P

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Dec 23, 2023

If you are a beginner and you wanna enhance your Exploratory Data Analysis (EDA) and Data Visualization skills with python, I think this is the best place to start off as you put all your learning skills at the end of the course's data analytics project , which is a very thoughtful step by google to make their potentials learners equip their resumes with great critical thinking projects. Thanks to Google !!

By Muhammad F A

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Jun 11, 2023

It was a very wonderful experience. In this course, I didn't only learn about Python as one of the strongest tools for data analysis and data science, but also learn the mechanism on how to conduct the Exploratory Data Analysis and create visualization using Tableau. This course will give you many insights on how to prepare your data before you start to analyze it deeper.

By John R

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Aug 31, 2023

This one for someone who just came from the previous certificate becomes a very challenging but enjoyable journey. You are not only applying python, but coming with solutions, solving problems, reading documentation and getting a structured mindset to tackle a wide range of obstacles. By far the most challenging and enjoyable with a lot of information.

By Stavros X

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Aug 15, 2023

Amazing course. The first true advanced course of the program that make me understand the significance of the two previous ones. Beautifully built-up knowledge pathway! I found every video, reading, and activity fascinating, and really helped me to learn a lot. Thank you!!!

By Brent A

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May 29, 2023

Phenomenal instruction. The level of depth is challenging in regards to the different methods shown for cleaning data and eliminating outliers but the format it is presented in is engaging. These course definitely

expanded my Python and Data Science knowledge.

By Jimmy P

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Dec 10, 2023

I thought this module is the best part of the whole certificate course, the instructor was so passion with everything he talked about and I can feel his deep loving for his data analysis job, and also his passion had passed to me.

By liam j

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May 27, 2023

I really loved the pandas side. I think the pandas section should contain more info about merging data though. I also think that Power BI should be introduced since the release of Fabric and the up and coming Co-Pilot

By James A M

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Aug 23, 2023

Very Helpful Course! The storytell methods described are really helpful to me. I have always had an issue with getting my point across but now I know where my problem was and have corrected it.

By Rob R

•

Sep 15, 2023

I really enjoyed this and look forward to going deeper into this. This course touched the basics...but they touched the right basics and have made me WANT to do more on my own.

By Marcelo P

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Apr 14, 2024

Understanding the importance of the EDA process is crucial in your data path. Check the content to go deep in understanding your data.

By Trung N P

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Feb 7, 2024

I’m so grateful for the excellence, well crafted and clearly delivered career-oriented course you have offered.

By Harish K

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May 30, 2023

Nice Content and Good Explanation with Great visualization techniques

Thanks for the Creators and Instructors

By Anthony H

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Sep 4, 2023

Very challenging but well worth the effort as it takes your skills and critical thinking to the next level.

By Muhammad N B

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Feb 12, 2024

Very well designed course for anyone having experience of any field willing to dive into data analytics.

By Thanh V

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Jun 16, 2023

This course offers excellent skills and approaches that are necessary for exploratory data analysis.