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Back to Go Beyond the Numbers: Translate Data into Insights

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

4.7
stars
699 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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76 - 100 of 114 Reviews for Go Beyond the Numbers: Translate Data into Insights

By YERRABELLI S

•

Dec 25, 2024

Excellent teacher

By Umme S N

•

Jan 29, 2024

Marvelous! Bravo

By Anitha m R

•

Apr 4, 2024

Awesome content

By Naseer A

•

Aug 9, 2024

Amazing Course

By Tofan S

•

Jul 28, 2024

user friendly

By Karim M

•

Feb 29, 2024

Great Course!

By Chandrashekhar D

•

Dec 10, 2023

outstanding..

By NAJAH B A R

•

May 27, 2024

very good

By Rod S

•

Sep 6, 2023

Excellent

By Janier R

•

Aug 8, 2023

Thank you

By Seif H

•

Apr 26, 2023

Excellent

By Josie T

•

Dec 24, 2023

engaging

By Saw H M K

•

Nov 4, 2024

thanks

By Justin H

•

Nov 26, 2023

Brutal

By Saptarshi S

•

Oct 25, 2024

good

By Bexruz N

•

Sep 1, 2024

best

By Trianto F

•

Aug 29, 2024

good

By sameh a

•

May 7, 2024

Cool

By KIDS L

•

Jun 17, 2023

best

By Jomarie O

•

May 12, 2023

nice

By Ertugrul G

•

Aug 20, 2024

a

By Carlos C

•

Jan 17, 2024

Positive: - The instructor is very clear in what he teaches and clearly explains when we're not supposed to know how to do things. - The parts that implement repetition in labs are extremely helpful and should be reinforced more. Having to convert things to datetime multiple times cements the structure a lot more easily. - Despite my criticisms (below) on the order information is presented at times, I do think I learned a lot. Negatives: - Once again you go into labs and are asked to use tools you haven't learned. Why am I introduced to things after having to find what to use in a lab? Parts of the reference guide for Python in Module 3 for "How to handle outliers" should have been presented earlier in the course. Some tools aren't taught at all and are expected to be found in the links to manuals provided throughout the lessons (which honestly are not very intuitive). - The labs are where I learn the most, but it takes me a lot longer than 1hr as a person who is new to Python and programming in general. There should be more emphasis on these. If you want people to figure out a solution with tools that haven't been presented, you should clearly outline that in the instructions during the different steps of the lab. It is deflating to wrack your brain trying to find a solution and then learn that it was not in the tools you've been taught so far, but not being told whether you should have explored outside of your taught knowledge. - During the Tableau presentation the instructor doesn't specify to change number of strikes to a dimension. It might be easy to miss the step.

By prateek v

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Apr 7, 2024

The content is exceptional. Coding in Jupyter notebook is quite good. However, I do think a review of contents could be done. There are times instructor missed to emphasize on important things, had to find answers in discussion forum. There are multiple instances where the video slightly differs from follow along guide. At some places the indexing within modules doesn't make sense. I preferred the previous Course where everything was much more organized. Where needed video would have a prompt to open follow along guide and navigate to specific section. Makes it much more convenient. I hope someone from the team reviews the contents once and fix these issues

By CHONG L

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Jun 1, 2023

The videos in this course are longer and harder to follow than the previous ones. The purpose of some of the EDA processes is hard to understand. I think they will become clear in the machine learning state. The instructor used many analogies to help understanding.

By Russell E B

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Jun 30, 2024

This is a pretty good course. The quizzes are a bit easy. And even though the Specialization has "Advanced" in title, it is not all that advanced. But I recommend it to get started after completing the "Data Analytics" Specialization from Google.