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IBM: Data Science Tools

4.3 stars
29 ratings

Learn about the most popular data science tools, including how to use them and what their features are.

Data Science Tools
7 weeks
3–7 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

33,150 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Feb 23
Ends Jun 30

About this course

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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can execute, their features and limitations and how data scientists use these tools today.

With the tools hosted in the cloud, you will be able to test each tool and follow instructions to run simple code in Python or R. To complete the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio on Cloud and demonstrate your proficiency in preparing a notebook, writing Markdown, and sharing your work with your peers.

This hands-on course will get you up and running with some of the latest and greatest data science tools.

Awards

Data Science Tools V2

At a glance

  • Language: English
  • Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated programs:
  • Associated skills:Jupyter, Data Science, Python (Programming Language), Jupyter Notebook, Watson Studio, Markdown, RStudio

What you'll learn

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  • List various tools used by data scientists and machine learning engineers
  • Describe various programming languages used by data scientists such as Python, R, Julia and SQL
  • Explain the various components of a data scientist's toolkit, including Libraries, Packages, Data sets and Machine Learning Models
  • Explain the features of Jupyter Notebooks and how to use them
  • Work with popular tools employed by data scientists including RStudio IDE and GitHub
  • Create and share a Jupyter Notebook
  • Navigate IBM Watson Studio and describe its features and capabilities

This course is part ofIBM Data Science Professional Certificate Program

Learn more 
Expert instruction
10 skill-building courses
Self-paced
Progress at your own speed
1 year
3 - 6 hours per week

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