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.
por Joseph G•
I learned so much in this course. I had no idea these tools were available in one place online. In preparation for doing the IBM Professional Certificate, I spent about a week installing programs and languages and stressing out about GUIs and IDEs. This course showed me multiple ways to get around all this and use IBM online tools.
por K L K•
A very good informative course! All tools of data science are discussed. A bit practical sense of few important open source tools is given nicely. You will uderstood that there are wide variety of tools for data science! Great one! This will push the beginners out of their theoretical zone to see the real information and tools.
por Jess M•
A lot of this is outdated since the IBM Watson stuff has been completely revamped, and the Zeppelin Notebooks tutorials were difficult to follow, since they seemed to have already been run when I went in, and therefore I couldn't tell what was function and what was output. But it's great to have all these free tools available.
por James L M•
This actually helps me since I have no background regarding the tools needed for development in Data Science. Week 1 and 2 are particularly helpful since it introduces a lot of tools that one could use. Week 3 is a bit promotional and week 4 is true challenge. The course really guides you on how to start jupyter notebook.
por Ankit T•
It was a great experience to learn the various open-source tool for data science. I have gained considerable knowledge of the Jupyter Notebook and IBM Watson Studio. It will be of great help for learners if the data science experience tool videos will be modified with IBM Watson Studio navigation and notebook creation.
por Isis S C•
Loved the course! It presents integrated environments where we can perform data analysis (+all previous and post steps) using multiple languages in open-source tools. IBM Skills Network Labs is perfect for learning, IBM Watson Studios enables collaboration and scalability, for enterprises. Super convenient tools!
por Frances B•
the course is great for people getting into the field of data science and have no clue where to start with resources for the filed. It helps build confidence and security knowing there are resources at our finger tips, for free, and with guidance from the the tutorial videos provided in this course. great stuff.
por Atal S S M•
Very informative on the open source tools available. It does get tricky sometimes to understand the instructions of the notebooks as the videos display an older version and the current website would have the updated version. IBM Cloud is a huge advantage to work on Python,R and Scala with spark kernels for free.
por Mike M•
Very beneficial, albeit somewhat painful , in getting the assignment done since the videos (at the time of this review) are not exactly correlated with current software (Watson v. Data Experience).
But hey, we are to be problem solvers, so that was just one minor hurdle to overcome and learn from in the process!
This course was intensive on tools used in Data Science. It was an overwhelming experience for I learnt to use resources on Github and understood how Jupyter notebooks are important in writing long codes. All in all , a great experience and would like to complete the full IBM data science specialization soon.
por Travis T•
It's a good overview of all the tools that can be used for data science. If you're following along with the IBM course, it gives you a good idea of what you could be using for your capstone class. They do not detail much of tools rather introduce them to you. It'd be up to you to delve deeper if you'd like.
por Nyaniso N•
A very gentle and slightly challenging introduction to the some of the best tools in the Data Science fraternity. Also, the added introduction to the IBM Watson Clouds tools was seriously interesting. Who knew you could just drag and drop files of refined data and you are on your way to "Model Building"?
por Luis G•
Astonishing course for learning the basics of the tools used for data science, open source tools and comercial tools, at the beginning it might be a bit overwhelming because of lots of terms that are unknown by most starters like me, but as the course goes on and if you are commited, it's a piece of cake
por CHIN-HUNG, Y•
Nice in introducing approaches to data science; however, some parts appears unnecessary to be mentioned right in the beginning. For example: Appache Zeeplin and Zeppling for Scala are more of courses in either intermediate or advanced level. Perhaps postponing it till database would be a better option.
por Elmer B E•
This is a very comprehensive presentation on the available tools for Data Science both Open Sources and that of IBM proprietary tools. As presented, you as a Data Scientist has the sole option which of these tools are fit for your data science studies. Very enlightening and full of thoughts to ponder.
por Isha C•
Good introduction to free and paid programs available for practicing and understanding data science! It shows detailed UI walkthroughs and tutorials, and gets you started setting up accounts that you will most likely use many years while learning data science and programming (R, Scala, Python, etc).
por Courtney B•
Love it! It's such a gentle introduction to the tools of the trade as well as the languages we need to learn in order to use them. The labwork is my favorite part. The only way you can learn anything interactive like this is by diving in and trying things out, and now all I want to do is learn MORE.
por Philipp R•
Great introduction to various tools offered by IBM. The course does not go into depths but rather shows what is out there. To really get the most out of this course, one needs to be motivated to explore the tools on one's own time. But that is a given in this field, I'd say. Therefore, five stars
por Mahesh M•
This gave me the brief introduction of Data science with IBM tools, the essential third party tools for Data scientists. Introductory knowledge on almost all data science related techniques is appreciable. One can enhance it completely by going through future courses in the same specialization.
por Sagarika S•
The course is amazing for beginners as well as for professionals for building the concepts. I am really thankful to all the instructors for delivering the concepts very clearly. I recommend this course to everyone who wants to learn the different tools to build their foundation in Data Science.
por Abrar M I•
This course did a great job of summarizing the coding and non-coding tools required for data science as well as highlighting the different levels of interaction with data and modeling and how collaboration is achieved as well as learning in the field. This was awesome, would highly recommend!
por Fiorella M•
This course is excellent to understand as an introduction the principal tools that are usted in the data science field. With this knowledge I have a more clear view on the tools I would like to investigate. I recommend this course for beginners with no clue of the tools usted in data science.
por Aman K C•
This was a really intuitive course with hands on experience on Jupyter Notebooks, Rstudio, Python 3.
It turns out to be the more I'll practice the more I'll learn and this course really turned out to be helpful as a stepping stone towards it. Thanks a lot for creating such an amazing course.
por Danesh T•
In the modern digital world transformation of world and the data science is very useful in our daily life activities and increases the quality of life and now a days the information is the wealth and it is used in the future career and so many applications of data science is used.
por Maksim M•
This course gives good practical understanding of the open source tools for data science, such as Jupyter Notebooks, Zeppelin Notebook, RStudio IDE, IBM Watson Studio. Now I know what they are and how to use them, although had absolutely zero idea about the matter before taking the course.