Offered By: CognitiveClass
Data Science Tools
Learn about the most popular data science tools, including how to use them and what their features are.
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Data Science
33.1k+ EnrolledAt a Glance
Learn about the most popular data science tools, including how to use them and what their features are.
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.
You will Learn:
- How to use various data science and data visualization tools hosted on Skills Network Labs
- How to use Jupyter Notebooks including its features and why it's so popular
- Popular tools used by R Programmers including RStudio IDE
- IBM Watson Studio including its features and capabilities
- How to create and share a Jupyter Notebook
Module 0 - Welcome and Course Introduction
Module 1 - Languages of Data Science
Module 2 - Data Science Tools
Module 3 - Packages, APIs, Data Sets and Models
Module 4 - GitHub
Module 5 - Jupyter Notebooks and JupyterLab
Module 6 - RStudio IDE
Module 7 - Watson Studio
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
- None
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Romeo Kinsler
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, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.

Svetlana Levitan
Svetlana Levitan is a Senior Developer Advocate with IBM Center for Open Data and AI Technologies, Svetlana has been a software engineer and technical lead for SPSS for many years. She works on open standards for machine learning model deployment PMML and ONNX. She holds PhD in Applied Math and MS in CS from University of Maryland, College Park. Svetlana loves to learn new technologies, share her expertise, and to encourage women in STEM.

Maureen McElaney
Estimated Effort
15 Hours
Level
Beginner
Language
English
Course Code
DS0105EN