A good course, in my opinion fundamental to step forward in Data Science projects, only one consideration, I thinkk it would be better to put in 2nd place of the degree , before of Tools for Data Science.

Very well explained, easy to digest and really paints the picture of a data scientist various activities and contributions within a project. I highly recommend this course, no previous knowledge needed.

Great overview of most popular data science tools, like Jupyter notebooks and numpy a really great entry point for using machine learning, learning about server services and applying them to businesses.

This course clearly describes the iterative process of Data Science Methodology which is mandatory for a Data Scientist. The course material was easy to follow and the final assignment was interesting.

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tic. It is impossible to understand the purpose of a science if you don't understand the problem and the approach to problem solving. And this is precisely what is achieved here.

Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!

This course covers the end to end cycle suggested framework that can be useful not only in Data Science but also in other Research Projects that manage information to create and deploy a solution.

It is a very important course to understand the procedures and thought processes behind data science. I strongly recommend it to those who are unfamiliar with data science or reserach methodology.

This was a clear and concise overview of the methodology and using the case study really helped (although sometimes it got a bit advanced considering this comes before actually learning models).

A very important course to develop a fundamental understanding of data science. Excellent in-course example to simplify the process of learning (think of it as a recipe in cooking). Enjoyed it.

Great Course. It was a simple course and to the point. It explained the concepts perfectly for future advancement. I think the theory in here could be applied to any problem data science or not

It's a very good course for getting the basic idea of the methodology of data science. It will help to get grip on how to proceed to a problem in a systematic manner for getting good results.

It was a good course with very easy to understand material and methodology.

In my opinion additional optional reading resources or case study links is required for this to be a 5 star course.

in this course step by step guide for beginner data scientists is illustrated with practical application and real examples with codes! best course in this specialization so far. Enjoy it :)

Very enriching course. I really liked the content of this course as it has guided me the basic framework of solving any data science problem. the assignment is also fun and enjoyable to do.

Content delivery was good, slides are awesome, lab assignmet , quiz questions are great for understanding the course, case study based learning helps to understan the concepts clearly.

Muy completo, y entendible acerca de cómo convertir un problema en un proyecto solucionable a través de la data, siguiendo simplemente unos pasos y pensando con un poco de creatividad.

This course is a great overview of the process of analyzing a data set. I feel a lot more ready for a Data Analysis job after this course than I did before. So glad I chose to take it.

P​urely the Methodolody of Data Science. It is good for those who want to know the big picture or the working flow of Data Science. It is necessary to take other courses to go deeper

Very helpful in helping students to understand the general methodollogy of data science and how the model can be iteratively improved for higher accuracy in production environment.

By this course you will be able to think like a Data Scientist. The methodologies explained in the course rebuilds my mind in thinking about how I should approach solving problems.

I thoroughly enjoyed this module and will go back to reread it several times over. This is the foundation of everything I will be doing in the future. I want to be grounded in it.

Love the CRISP-DM methodology and the examples given to illustrate each step. Definitely needs to be a standard procedure for any company wanting to develop data-driven analysis.

Very well done course that explains all the stages of a data science project with use of examples (case study). Reading and Jupyter Notes are also very well done and descriptive.

It don't just give you the methodology at high level, it also shows you the codes you would write for each step so you get a solid feel of how the analysis and execution happens.