Amazing, you get to see almost every aspect of data science.

It is true that you won't get deeepeeeer, but this course allow you to not fear any kind of data science. That's amazing.

This course is very enlightening. The techniques demonstrated in this course are critical for gathering raw data from various sources and turning it into useful data for analysis.

I really liked this course and believe that my work, although seemingly noob-ish, will get much better as I see others works from the peer review and examples noted in the lessons.

So knowledgeable and interesting course. I have learned much about data cleaning and getting from different sources. Finally thanks to coursera team for giving us the opportunity.

This is a very well put together course. It teaches the basics of data cleansing and how to setup data for modeling--by far the most foundational technical aspect of data analysis.

How to get a clean the data is a very important knowledge for the future data scientist and data analyst. For me this course was very important I very recommend take this course.

Great course on tidy data. Very useful in understanding how to use different types of data (csv, XML, API) and how to manipulate the data so that you can perform analyses on it.

Excellent course, and quizzes and lecture were very teaching. But some materials needs to be updated up to date , like subsetting columns in data.table the slides were absolute.

Great ready-to-use skills for common tasks of a Data Scientist. Lays the foundations for further self-development in the topics taught. Heavy on R. Very challenging assignments.

really thorough class... come prepared to learn and be patient as your going to get your hands pretty dirty reading data, cleaning it and manipulating the result sets with R

I think this course is really good, the instructors give you a lot of tools to handle data bases! I would recomend this course to any person that wants to learn about this.

Super useful, there are so many raw data in the practical world, which are needed to be cleaned, so that the analysts and other people can easily get information from data.

I use so much of what I've learned here on a day to day basis! Using the suite of functions from ggplot, dplyr, plyr and others has greatly reduced my data management time.

This course was very useful, informative and interesting. However, I did feel that the course assignment seems to be, perhaps purposefully, but a bit unnecessarily vague.

The challenging quizzes and assignments are a main reason why this course is so great! This course truly ensures that you truly understand and implement the videos.

I have found this course very useful to gain a nice overview of the main tools to obtain and clean data. Moreover, for me it was challenging, which is always a plus.

Very interesting. Global view to process Data and try to explain with very useful techniques the processing or cleaning data with regular expressions. I enjoyed it!

A great course in which many important concepts and techniques are covered. It also covers many handy tools/libraries that one can use to clean and manipulate data.

Very intense and covering a lot of material - After about an year from having the course and with a different understanding, this is probably the course to revisit.

Muy buen curso y con buena evaluación de los temas mediante asignaciones varias con estudios en el mundo real que lo preparan para estar analizando trabajos reales

Great course! I loved it. It's just informal enough and rigorous enough. The pace is enjoyable and the experience of the instructor carries well.

Highly recommend.

Useful general course on tidying data and learning to import into R from various sources. Doesn't get into sequencing data import, but looks at other common ones

This course was very intense and not easy but over all, after doing all the work! Oh man I feel I have way more confidence in my R skills and Data understanding.

Excellent course. You will learn about concepts of 'clean' or tidy data and apply it in R. One of the most important, yet often ignored, aspects of data science.

It is an excellent exercise to work on data cleaning and pre-processing. Also give me the great chance to read through the paper by Hadley Wickham on Tidy Data.