Feb 12, 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.
Aug 19, 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."
创建者 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.
创建者 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.
创建者 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.
创建者 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
创建者 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
创建者 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.
创建者 ONG P S•
Jan 19, 2020
Very practical and knowledge learned can be applied into my works as auditors. This can benefit any fields involving using data.
创建者 Donald 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.
创建者 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
创建者 PRAKASH K•
Jul 13, 2020
I strongly recommend this course ,it focuses on reproducible research which is equally an important aspect of data analysis.
创建者 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.
创建者 Mathew K 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.
创建者 Amanyiraho R•
Jan 13, 2020
Very interesting and tackles a very important issue that Data scientists always miss-out, reproducibility of your project
创建者 Azat G•
Jan 24, 2019
Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.
创建者 Anusha V•
Jan 3, 2019
Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.
创建者 Adrielle S•
Apr 3, 2016
Muito completo. Inglês claro. Muitos exemplos. Chega a ser repetitivo em algumas aulas mas, antes sobrar do que faltar!
创建者 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!
创建者 Monica Z•
Dec 11, 2020
Very challenging. However, every step in this specialization improves my knowledge and the way of solving problems.
创建者 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.
创建者 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.
创建者 Lee Y L R•
Feb 1, 2018
Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.
创建者 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.
创建者 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.
创建者 Courtney R•
Oct 7, 2019
I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.
创建者 Thiago M•
Aug 12, 2019
course material and projects help a lot in learning and tips on how to better document research and projects