GitHub on Mac/Linux - Part 2 (Optional)

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IBM
4.6 (18,115 ratings) | 130K Students Enrolled
Course 2 of 9 in the IBM Data Science Specialization
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Reviews

4.6 (18,115 ratings)
  • 5 stars
    69%
  • 4 stars
    22%
  • 3 stars
    6%
  • 2 stars
    2%
  • 1 star
    1%
NS

Jun 30, 2019

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.

SH

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.

From the lesson
Open Source Tools
This week, you will learn about three popular tools used in data science: GitHub, Jupyter Notebooks, and RStudio IDE. You will become familiar with the features of each tool, and what makes these tools so popular among data scientists today.

Taught By

  • Romeo Kienzler

    Romeo Kienzler

    Chief Data Scientist, Course Lead
  • Svetlana Levitan

    Svetlana Levitan

    Senior Developer Advocate with IBM Center for Open Data and AI Technologies

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