To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!
Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.
By Neelabh S•
Really nice introductions to these amazing tools such as Jupyter Noteboos, Zeppelin, IBM Watson Studio and RStudio IDE. Very easy to grasp and the final project helps practice all the basics in Jupyter notebook using some Python code.
By Jafed E G•
I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand
By Jason K•
Very good explanation of all tools that is available to users to enable them to work effectively. The labs also proved helpful with practicing and getting familiar in terms of navigation and getting use to the different environments.
By Mateusz K•
Nice review of existing open source tools and free to use web services implementing those tools. Personally I would also enjoy some introduction to either how to set up those open source tools on a personal computer or private cloud.
By 053 V N•
this course I good enough to under stand which tools are applicable in data processing in data science . thanks Coursera for providing such a course that was very funy I enjoyed my valuable time learning with Coursera and faculty
By Suraj R G•
Fantastic course it was. I got overview of most of the open source tools for Data Science.
The Assignment at the end of the course was also interesting as it summarizes all the things we learned.
Thank you for such awesome content.
By Daniel F d P•
Eu adorei esse curso. Me ensinou muito mais do que apenas ferramentas de código livre para data science. Aprendi também sobre computação na núvem e ganhei vivência na IBM Cloud, além de aprender sobre como baixar dados públicos.
By Sakiru Y•
The course is quite technical but very educational and instructive. Though I got a bit confused when I created the Watson Studio, because the platform was different from what the instructor used. But it is an interesting course
By Aman T•
This course was good It will teach you various open source tools that are being used in data science fields like RStudio, Jupyter notebooks, Scala, Hadoop,Apache spark etc. I would definetly suggest you to take this course .
By DEV A•
Just enough to know the different types of open source tools that can be used to data science. to learn the tool completely, we need to refer to many tutorial materials within.
Good Introduction session for tool applications.
By Avirup C•
The course is exceptionally good in order to introduce you various details about the tools that you require for Data Science Analytics.
Exceptionally well made support by IBM and Coursera is as a whole best for these courses.
By Eric G•
Great course and the tools provided are very useful. You have to really work by yourself to read and understand the tools though, because there is no way other than practice to learn the various notebooks and how they work.
By Moonsuk S•
I am novice to this field. Nevertheless, I did not have much troubles in catching up the class because the contents of this courses are very well organized and the level of the class was well adjusted. Thank you very much!
By Marceline C M•
I loved the practical approach of the course. It's not just listing of tools but step by step application which makes me more confident-I know exactly where to fetch each tool I need in a Data Science Project.
By Jatin S•
The Tools which were mentioned in the course are really helpful and important.
Through this course, you can get to know about various tools used in Data Science with their use and explanation. I really liked this course.
By Apurva R•
Though the interface in the videos were little outdated, the IBM professionals are working on it to make it better. The style of teaching is incredible. Extremely responsive team. Thanks for giving us a chance to learn.
By Devineni M S S s•
this was a very good course, to kick start the basics of various IDE's and how to use them on the cloud. This course is very helpful in providing knowledge and outlook of many new technologies that i am not aware of.
By Gilmar N•
I really enjoyed this course! I had a very poor knowlegde of Zepplelin for instance, now I even consider using that tool more often! Besides, learning how to better use Jupyter is a great experience worthy the time!
By Ramesh B•
I did learn something about Data Science tools but not thoroughly. Hope to learn further on the tools and its application. I know now that IBM Watson Studio is great to do Data Analytics. Thanks to the instructors.
By Max P•
Some videos are of inferior quality. And subtitles at times inconsistent with what people in video are saying. Also in R lab some insonsistencies, such as the code that should be added in the end is already added.
By Josias S•
Excellent content for someone who has no programming background! I will recommend to anyone to sign up cause even if you might doubt that you don't know much, by the the end of the course you will feel like a Pro!
By Muhammad U N•
This course introduced me to the open source tools available for data scientists. The good thing about this course is introduction to multiple tools rather than a single tool and exercises to practice on the tool.
By Anish K•
This course has given me basic understanding of tools used in data science and its uses. It has given me confidence that folks who don't have computer science background can also master the data analysis skills.
By Adenuga B o•
This track has exposed me to tools i never knew existed as a beginner, I have learnt how to use them and I am pleased to have gone through the track, my gratitude to my teachers and IBM for putting this together
By Anirudh G•
We get to learn the basics of all open-source data science tools and their working in IBM Watson Studio and IBM Data Science Workbench. Tools we learn here are Jupyter Notebooks, Zeppelin Notebooks, R Studio IDE