AA
12 févr. 2016
My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.
RR
19 août 2020
A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."
par Keidzh S
•24 avr. 2018
Thank you so much. Representatives lessons in my opinion very effective. I learn so much about html and markdown files in this course.
par Leo F
•28 févr. 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.
par Luz M S G
•6 oct. 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.
par Arjun S
•27 août 2017
Great stuff. Glad to have the course make us create an Rpubs profile and publish research. Recommended strongly for data scientists
par Daniel C J
•14 nov. 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
par Omar N
•8 nov. 2018
Really good module/course, gives you a glimpse into real world implementation of data science and the challenges involved with it.
par ONG P S
•19 janv. 2020
Very practical and knowledge learned can be applied into my works as auditors. This can benefit any fields involving using data.
par Donald J
•22 janv. 2018
These are important skills for a data scientist and I'm glad there is a full 4-week course dedicated to reproducible research.
par Richmond S
•29 sept. 2016
I struggled in getting the final project right but it helped me understand the course better. Thumbs up reproducible research
par PRAKASH K
•13 juil. 2020
I strongly recommend this course ,it focuses on reproducible research which is equally an important aspect of data analysis.
par Glenn W
•4 mars 2019
Favorite course so far. Really enjoyed working on the projects. They were very helpful in helping to reinforce the material.
par Mathew K E
•30 mars 2021
This course has been an eye-opener for me and going forward, it would be an indispensable tool in my research activities.
par Amanyiraho R
•13 janv. 2020
Very interesting and tackles a very important issue that Data scientists always miss-out, reproducibility of your project
par Azat G
•24 janv. 2019
Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.
par Anusha V
•3 janv. 2019
Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.
par Adrielle S
•3 avr. 2016
Muito completo. Inglês claro. Muitos exemplos. Chega a ser repetitivo em algumas aulas mas, antes sobrar do que faltar!
par Krishna B
•30 mai 2017
towards the end of week 1 lectures we can see all the parts of this specialization coming together in a very nice way!
par Monica Z
•11 déc. 2020
Very challenging. However, every step in this specialization improves my knowledge and the way of solving problems.
par Prem S
•2 août 2017
Nice course,especially it gives you a general idea and foundation on r markdown files if you already know R studio.
par Federico A V R
•27 juil. 2017
This topic is relevant to the field, yet few institutions offer courses on it. Great knowledge, highly recommended.
par Lee Y L R
•1 févr. 2018
Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.
par Ann B
•14 mars 2017
I think this topic is sometimes overlooked, but very necessary. This course did a good job of covering the topic.
par Emily S
•17 mai 2016
I think this is an essential course that more people should take. Reproducibility is a huge issue in many fields.
par Courtney R
•7 oct. 2019
I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.
par Thiago M
•12 août 2019
course material and projects help a lot in learning and tips on how to better document research and projects