Apr 25, 2019
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!!!!
Feb 01, 2019
All the tools required for ML kick starting was explained very clearly and it helped me a lot in building the understanding of what tools need to be learnt in the field of ML and Data Science.
교육 기관: Apurva R•
Mar 25, 2020
Though the interface in the videos were little outdated, the IBM professionals are working on it to make it better.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.
교육 기관: Devineni M S S s•
Oct 05, 2019
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.
교육 기관: Gilmar N•
Feb 19, 2019
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!
교육 기관: Josias S•
Apr 09, 2020
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!
교육 기관: Muhammad U N•
Mar 14, 2019
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.
교육 기관: Adenuga B o•
Apr 27, 2020
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
교육 기관: Anirudh G•
Aug 06, 2019
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
교육 기관: KAIRAV T•
Apr 14, 2020
An amazing course providing great exposure to data science basics and tools for data science. The amazing explanation regarding the benefits of the cloud computing in the world of data science are dope as well.
교육 기관: Ruhul A•
Mar 27, 2020
This seems to be a good start to know the tools in the field and have a brief introduction on each one of them, must for someone who is looking for a trend which Data Science had and has in past and present.
교육 기관: Abhimanyu S•
Nov 04, 2018
Very nice course. This course gives a detailed introduction to the IBM Watson Studio along with other important tools for Data Scientists. It's a must do course for all beginners in the field of Data Science
교육 기관: Anteneh A Y•
Apr 13, 2020
I have made a rock foundation after taking this class! It gives you a guide that you can expand it with other resources over the internet and books. It is an excellent guide and content is also fun as well!
교육 기관: Zayani M•
Sep 10, 2018
It's easier than it looks. I was anxious when the mini lessons started using jargon that was unfamiliar to me. But when I started watching the demonstrations and doing the exercises, it all made more sense.
교육 기관: Giulio C•
Apr 13, 2020
It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.
교육 기관: Stella•
Mar 01, 2020
Good to overview web-based data analyzing tools like Jupyter notebook, Zeppelin notebook and R studio IDE by getting access to virtual environments like Skills Network Labs and IBM Watson studio.
교육 기관: Mian M A•
Nov 29, 2019
This course helped me finding open source tools. I knew about Jupyter Notebooks, but I also got to know more tools. Further, I got IBM subscription too, it would definitely help me in my work.
교육 기관: shiva k p•
Dec 16, 2019
The videos in this course are outdated and the content in videos doesn't match with the reality because the videos are old and Watson studio got updated. Course content must be updated ASAP.
교육 기관: Evgeniy V•
Sep 18, 2019
Useful, quite a bit of practical. I've learned a lot of new tools and possibilities to use them for free; although based on IBM infrastructure, they're open source and may be used everywhere.
교육 기관: Pablo M•
Jun 04, 2019
Does a good job of showing areas to obtain access to use Python, R, and Scala. You can however tell they're pushing IBM products when in reality there are many other options such as Anaconda.
교육 기관: Orestis P•
May 02, 2020
very good structured and easy explained. most important: you can practice the basics of a (juoiter,zeppelin and RStudio IDE) lab while the instructor is giving an overview of the environment
교육 기관: Harsh N M•
Dec 19, 2019
Great course to gain knowledge from.One must spend a good amount of time in order to learn the basic tools of data science and thus won't find it difficult to work in data science in future.
교육 기관: Todd J•
Sep 19, 2018
Another Great class. Really introduces you to new tools that out there, not just for Data Scientist to use, but for anyone that has the use for R or Python coding etc. Loved the course.
교육 기관: Daniel L•
Oct 19, 2019
Impressed by those notebooks or development environment, and its availability on Web; very practical to document the method used in a data study, integrating programming with documenting.
교육 기관: JOSHY J•
Sep 07, 2019
Good Course. Help you understand the most used open-source tools for Data Science. It also introduces IBM Watson Studio which is the best cloud-based collaborative tool for Data science.
교육 기관: Thong T•
Apr 29, 2020
Thank this course for letting me know there are online tools for data science, which help collaboration anytime and anywhere. It is trusted because it is from IBM, a well-known company.
교육 기관: Berkay T•
Aug 28, 2019
Brief introduction to what cloud platforms available to execute coding in different kernels. You also get an idea on how you will be analyzing data with what sort of tools and outcomes.