Artificial Intelligence & Data Science
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Tools for Data Science by Coursera

Course Cover

5

(8)

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Course Features

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Duration

18 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

18 hours

Course Description

What are the most widely used data science tools? How do you use them? And what are their best features? This course will teach you about Jupyter Notebooks and JupyterLab as well as RStudio IDE. Git, GitHub and Watson Studio. Learn about the purpose of each tool, which programming languages they can run, and their limitations. You will be able test the tools and follow the instructions to run simple codes in Python, R, or Scala using the Skills Network Labs cloud-hosted tools. You will complete the course by creating a final project using a Jupyter Notebook from IBM Watson Studio. This will demonstrate your ability to prepare a notebook, write Markdown and share your work with peers.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Describe the languages, tools, and data used by data scientists, including IBM tools focused on data science

Create and manage source code for data science in GitHub

Describe the features of Jupyter Notebook and RStudio IDE that make them popular for data science projects

Explain how IBM Watson Studio and other IBM data science tools can be used by data scientists

Course Instructors

Aije Egwaikhide

Senior Data Scientist

Aije Egwaikhide is a Data Scientist at IBM who holds a degree in Economics and Statistics from the University of Manitoba and a Post-grad in Business Analytics from St. Lawrence College, Kingston. Sh...

Svetlana Levitan

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

Svetlana Levitan is the instructor for this course

Romeo Kienzler

Chief Data Scientist, Course Lead

Romeo Kienzler holds a M. Sc. (ETH) in Information Systems, Bioinformatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering...

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