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.

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.

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.

Unfortunately, this course was not what I expected, it was poorly organized, and shallow, the Tableau part is very rushed and full of mistakes. I hope this will be considered.

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

2 stars to raise some attention, hopefully(highly unlikely though).

Discussion forums are full of zombies. Learners either put empty strings or meaningless signs on discussion topics. Learners' questions never got answered, if you post a question regarding learning material, it is guaranteed your post either gets ignored or get some bot messages. Very google like--we don't give a damn about forums, we already did what we did.

This course was very poorly organized and difficult to follow. There was a very wide range of topics covered with very little depth. The quizzes don't test you for key knowledge. The exercises are worded in ambiguous ways that make it difficult to know what is expected. I was disappointed because I was excited about this course and I feel like it was very rushed. Expect to spend a lot of time off the Coursera platform learning the content.

Instructor jumps between libraries without teaching each construct of code. His idea of teaching is to give me a summary of what a line of code does without previously having covered the syntax. It's as if he thinks he serves as just a guide and I need to run to the forums and research on my own albeit he gets paid for this. I pay to save time.

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.

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.

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

je remerci toutes l'equipe , vous etes formidables

While this will walk you through the syntax of doing some basic analysis using Python, it will not explain why you are doing it. Same with Tableau. The labs tell you to do things to generate visualizations, but doesn't explain why Tableau needs things done a certain way. Basically, you may be better off Googling thing information ironically.

Thank you so much for your guidance and encouragement throughout this course. Your passion for EDA and data visualization was truly contagious, and it made the learning experience both engaging and impactful. I now see data not just as numbers, but as stories waiting to be uncovered—and that perspective has transformed how I approach analysis. I’m grateful for the foundation you've helped me build, and I look forward to applying these skills with the same curiosity and enthusiasm you’ve instilled in me. Your words mean a lot, and I’ll carry them with me as I continue this journey into the world of data.

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.

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.

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 !!

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.

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.

Excellent course. I learned a lot about EDA with Pandas in this course, as well as data visualization with Tableau. This course is highly recommended for data science enthusiasts. But keep in mind that the less you know about Pandas, EDA, and visualizations with Matplotlib and Seaborn, the more time you'll need to dedicate to this course.