RG
4.0Reviewed Mar 27, 2020
It's a good introductory course to know all the open-source tools available for data science. However, it will not teach you how to code for these tools apart from introducing a few basic lines.
Tools for Data Science
In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Status: Python Programming
Status: Scikit Learn (Machine Learning Library)
BeginnerCourse16 hours
Featured reviews
FC
4.0Reviewed Nov 5, 2019
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.
MA
4.0Reviewed May 19, 2023
The course is overwhelming for a beginner with no experiecne of programming. The examples given in the class seem difficult and should have been of a lower difficulty level to keep the hopes high.
RJ
5.0Reviewed Oct 7, 2021
Great course with practical approach to tools that come handy beside data science with python such as git and github, Some basic R coding and a great introduction to IBM Watson studio and cloud.
GC
5.0Reviewed Apr 12, 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.
LK
5.0Reviewed Aug 29, 2020
This course is awsum and well explained. Some portions needs to be updated based on the current platforms. i.e Lab instructions should be inline with the current screen, e.g. Watson Studio.Thanks !
TY
5.0Reviewed Sep 25, 2020
The course is interesting. It presents large spectrum of tools. It could be more helpful to provide general information on different tools and focus on few of them such as R, GitHub for example.
BF
5.0Reviewed Jun 13, 2024
Great introductory course to show DS enthusiasts the multitude of available tools. Part of every solution is picking the right tool for the job, therefore this course is important to pay attention to!
FD
4.0Reviewed Nov 17, 2020
Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.
LD
4.0Reviewed Apr 25, 2021
Great course, I would really encourage everyone to go through, however videos about Jupyter Notebook or other tools were so fast I wasn't able to remember all the information. Anyway great course.
DH
4.0Reviewed Sep 21, 2020
Gives you a good idea and overview about different tools but can be overwhelming because of the amount of new information and some videos are not up to date. Week 3 especially had some weak videos.
RR
5.0Reviewed Apr 24, 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!!!!