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