It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
By Glauco P S•
I do understand why they used automated videos in order to keep all the material as updated as possible, however it is a strange experience.
By Judith W•
It is a good course to get familiar with the basics, however, I would have liked a little more actual content. Week Four I enjoyed the most.
By Suryakant S•
I liked the course as it helped me to understand the basics of R programming including the installation of R studio and linking it to GitHub
By Leul B•
Pretty great introductory course on types of data analysis. I can't wait to see how this builds in the future courses of the specialization.
Nice course for Beginners, No complains regarding course material, however there is little bit audio issue in some slides as it is bit low.
By Peter E•
Great Course! Overall I would recommend. Had a little bit of trouble b/c I am using a Mac but after a few Google Searches I was on my way!
By Brandon P•
Great course! I would recommend compressing the audio on the video presentations so it's easier to hear and more consistent in volume level.
By ashika g•
This course is nice kick start for the upcoming courses but the course could have been even more interactive . over all nice experience .
By Kadimisetty H S P•
This course helps many of us to get started with R and R studio. It also explains about some famous terms in data science and statistics. T
By Chloé S•
Everything was perfect except the Git and Github part. It was confusing. I ended up not using what it has teached me to pass the final exam
By Girish V V•
Quiz in final submission related to usage of toolbox Rstudio, like loading new packages will add more value and will help the learners also
By Francesco M•
Good introduction on Data science specializationi. I highly recommend to all people that would like to know more about this fantastic world
By John W•
I knew most of the material in this course already, but I thought it was a good introduction to some of the tools that data scientists use.
By Olivera D•
The automated voice of the lectures is dehumanized. It is less productive and focusing learning from a machine, but the material was good.
By Zengqi L•
I wish the instructors can be more clear with the Git and Github part. I still don't fully understand how to use Github for various tasks.
By RHR P•
The course is very nice and provides all that you need to get started on Data Science. Looking forward to the next set of courses. Thanks!
By John T M•
It was a good start and overview. The robot voice didn't always read correctly. RStudio has changeds since slides were made. Mostly good.
By Jonathan H•
Material is awesome! Clear and simple, with great examples!
Questions at the end of the modules are confusing sometimes, could be improve!
By Syam P V•
Good crash course on setting up all the toolbox necessary for a data scientist. The quiz could be more difficult than it is designed now.
By Arthur G•
In the course they use some tools' older versions and, for example, some Git commands shown on video are different in newer Git versions.
By Anand S•
Informative and helps people like me who are willing to learn from scartch. The course content though can do with a little more updation.
By Mallik T R•
This course is very good for introduction to Data Science toolbox . But there are some typing mistakes in the subtitles in some videos .
By Boris K•
Простейший базовый курс, не требующий никакой предварительной подготовки и минимум усилий. Указано 4 недели, по сути проходится за день.
By Chris W•
This was a very professionally done course. It is *very* introductory, which is either good or bad, depending on how you feel about it.
By Sichen L•
it introduces the basic tools that are frequently used in data science. However, it is rather baisc and the course did not go in depth.