What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
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來自OPEN SOURCE TOOLS FOR DATA SCIENCE的熱門評論
Tools are fantastic and will make a significant contribution to my education. Videos need to be updated for changes to Watson Studios. Support from IBM on their cloud services should also be improved.
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!!!!
It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.
There was a problem with the connection to R lab, never fixed. Also, some tutorials are outdated. These are the negative parts and why I give four stars. Other than that I like the course so far.
Excellent introduction to a variety of open source tools available and commonly used by Data Science Professionals. Some of the video material is slightly outdated due to updates to the platform.
Everything was good, except the stuff with Zeppelin notebooks. That was just confusing and it felt like there were large chunks of explanations missing for people with no programming background
This course is very nice to understand Python, Zappelin and R Studio basics on code and concepts, in which you will get hands on along with creating a free IBM Cloud and Watson Studio account.
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.
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.
This is a fast paced course. Where all open source tools required for data science are introduced.\n\nThe learner has to take up self initiative to gain deeper knowledge regarding this tools.
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.
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.
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.
This course introduced me to some great virtual environments to train my skills in data science. I'm now more familiar with these tools and ready to use them in more advanced applications.
overall, the course is great, but since the IBM environment changed, videos do not correspond to exercises. It would be good to add reading materials clarifying differences in more detail.
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.
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.
Pretty nice introduction. A short course, don't expect anything too technical, but i think in a world of heavy and long MOOCs, its not a bad thing to start off with a lightweight one :)
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.
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.