RG
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Great topic which is discussed well with a good case study. I'd like to see more up-to-date content and more detailed analytical techniques. However, it's a nice introduction!
IM
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Without taking this course wouldn't have fully understood the importance of reproducible research in data science. Thank you so much. I recommend this course for all data scientists.
By Nino P
•May 24, 2019
To be a data scientist you must use RMarkDown. Here you learn how to use it. A must do course for data scientists and highly valuable.
By Keidzh S
•Apr 24, 2018
Thank you so much. Representatives lessons in my opinion very effective. I learn so much about html and markdown files in this course.
By Leo F
•Feb 28, 2017
One of my favourites. The course is easy to follow and the idea of having a self-contained and reproducible document is very powerful.
By Luz M S G
•Oct 6, 2020
It was a good experience. The final project has been the most challenging that I have had in the specialization, but I learned a lot.
By Arjun S
•Aug 27, 2017
Great stuff. Glad to have the course make us create an Rpubs profile and publish research. Recommended strongly for data scientists
By Daniel C J
•Nov 14, 2016
Great course. A must for every analyst for its simple tips on reproducibility, which can go a very very long way at work or school
By Omar N
•Nov 8, 2018
Really good module/course, gives you a glimpse into real world implementation of data science and the challenges involved with it.
By Thomas
•Jan 19, 2020
Very practical and knowledge learned can be applied into my works as auditors. This can benefit any fields involving using data.
By Don J
•Jan 22, 2018
These are important skills for a data scientist and I'm glad there is a full 4-week course dedicated to reproducible research.
By Richmond S
•Sep 29, 2016
I struggled in getting the final project right but it helped me understand the course better. Thumbs up reproducible research
By PRAKASH K
•Jul 13, 2020
I strongly recommend this course ,it focuses on reproducible research which is equally an important aspect of data analysis.
By Glenn W
•Mar 4, 2019
Favorite course so far. Really enjoyed working on the projects. They were very helpful in helping to reinforce the material.
By Mathew E
•Mar 30, 2021
This course has been an eye-opener for me and going forward, it would be an indispensable tool in my research activities.
By Amanyiraho R
•Jan 13, 2020
Very interesting and tackles a very important issue that Data scientists always miss-out, reproducibility of your project
By Azat G
•Jan 24, 2019
Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.
By Anusha V
•Jan 3, 2019
Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.
By Adrielle d C S
•Apr 3, 2016
Muito completo. Inglês claro. Muitos exemplos. Chega a ser repetitivo em algumas aulas mas, antes sobrar do que faltar!
By Krishna B
•May 30, 2017
towards the end of week 1 lectures we can see all the parts of this specialization coming together in a very nice way!
By Monica Z
•Dec 11, 2020
Very challenging. However, every step in this specialization improves my knowledge and the way of solving problems.
By Prem S
•Aug 2, 2017
Nice course,especially it gives you a general idea and foundation on r markdown files if you already know R studio.
By Federico A V R
•Jul 27, 2017
This topic is relevant to the field, yet few institutions offer courses on it. Great knowledge, highly recommended.
By Lee Y L R
•Feb 1, 2018
Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.
By Ann B
•Mar 14, 2017
I think this topic is sometimes overlooked, but very necessary. This course did a good job of covering the topic.
By Emily S
•May 17, 2016
I think this is an essential course that more people should take. Reproducibility is a huge issue in many fields.
By Deleted A
•Oct 7, 2019
I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.