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 Pierre S
•11 avr. 2017
I think this not a complicated course but is absolutely fundamentals of proper scientific principles which are so often lacking in many data science/analytics projects.
par Juan P L R
•25 sept. 2020
Great course to learn about reproducible research in R, using knirt and RPub. Excellent course and carefully designed to complement the Specialization of Data Science.
par Tseliso M
•11 nov. 2017
Reproducibility is one of the key elements of modern scientific method. The course was very informative and introduce ideas I did not know before, but are crucial.
par Christian H
•10 nov. 2016
This course helped me realize why reproducible research is absolutely necessary, and gave me the tools to implement reproducibility in my work. Project was great.
par Himanshu R
•25 janv. 2018
A good informative course to inform about importance of "Reproducible Research", also a good one for practicing code writing and publishing in RPubs and Github.
par Joshua B M
•4 mars 2016
This class's R markdown material taught me to efficiently convey and market data analysis to non-specialists of data. It was immediately valuable to my career.
par Subramanya N
•12 déc. 2017
Good info on RStudio & RR.
I can easily figure out who has attended this course by their methodical nature and work when I see Kaggle competitions. Great job!
par Johann R
•7 juin 2017
A handy course to do when you have to create and submit reports with calculations and code. Learn the basic principles of report writing and report structure.
par RR A I
•22 sept. 2020
Though I could not solve all course projects on my own, I at least understood the techniques and enjoyed doing the course greatly. Thanks to the instructors
par Camilo Y
•10 janv. 2017
I found all the topics of this course important. Not only for my professional career but also for everyone who is involved with data and science in general.
par Andrea G
•11 mai 2020
Very important course. Not so many fancy analysis but it introduces to Markdown and explains well what does it mean to do data science within a community.
par Devanathan R
•7 févr. 2016
a very important part of data analysis. I especially found the case study in week 4 to be of tremendous interest highlighting the real world applications.
par Charles M
•25 avr. 2019
Great course. This and the previous course in the data scientist specialization are extremely practical and I've found immediate utility in my career.
par Marco I
•20 sept. 2018
Very interesting, the fact that our research procedure can be explained and showed to other to reproduce, validate and work on top of it is fantastic.
par Jessica R
•11 août 2019
Very useful in bringing together skills learned in the earlier courses of the Data Science specialization: R programming, R Markdown, knit, RPubs.
par Arturo P
•22 juin 2021
A relly nice course, it is not really difficult at all but it's really useful overall for researchers and making reports, i recommend it so much.
par Connor G
•30 août 2017
Very important subject matter taught well. My only qualm is that the final project was more difficult than I expected it to be given the content.
par Praveen k
•18 oct. 2018
Good course. Examples given throughout the course are biological based so it is little hard to understand completely because they are technical
par Marco B
•5 déc. 2017
this course is incredibly useful!
in my job i practice data analysis everyday and this course helped me to do everything in a more efficent way!
par Charly A
•26 nov. 2016
Excellent content and plan. The delivery is fantastic and the professor's explanatory clarity is top notch. I highly recommend this course.
par Warren F
•16 août 2016
Slightly less information than the previous courses in DS spec but important for someone who has not done scientific research in the past.
par Prairy
•17 mars 2016
Excellent course that is both well presented and very clear, providing many examples and opportunities to practice throughout the course.
par Tine M
•22 janv. 2018
Very interesting course, I was able to apply what I learned in the previous courses of the specialization, and that was a good exercise.
par Anirban C
•15 août 2017
Nice course! It helped me to understand the concepts of markdown and related R modules. The assignments were challenging and fun to do.
par Nino P
•24 mai 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.