Tools for Data Science at Coursera Overview
Duration | 22 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Tools for Data Science at Coursera Highlights
- 36% started a new career after completing these courses.
- 39% got a tangible career benefit from this course.
- 20% got a pay increase or promotion.
- Earn a shareable certificate upon completion.
Tools for Data Science at Coursera Course details
- What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
- LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
Tools for Data Science at Coursera Curriculum
Data Scientist's Toolkit
Course Introduction
Languages of Data Science
Introduction to Python
Introduction to R Language
Introduction to SQL
Other Languages
Categories of Data Science Tools
Open Source Tools for Data Science - Part 1
Open Source Tools for Data Science - Part 2
Commercial Tools for Data Science
Cloud Based Tools for Data Science
Libraries for Data Science
Application Programming Interfaces (API)
Data Sets - Powering Data Science
Sharing Enterprise Data - Data Asset eXchange
Machine Learning Models
The Model Asset Exchange
Practice Quiz - Languages
Practice Quiz - Tools
Practice Quiz - Packages, APIs, Data Sets, Models
Graded Quiz
Open Source Tools
Overview of Git/GitHub
GitHub - Getting Started
GitHub - Working with Branches
Git and GitHub via command line (Optional)
Branching and merging via command line (Optional)
Contributing to repositories via pull request (Optional)
Getting Started with Jupyter Notebook
Getting Started with JupyterLab
Jupyter Architecture
What is RStudio IDE?
Installing Packages and Loading Libraries in RStudio IDE
Plotting Within RStudio IDE
Practice Quiz - GitHub
Practice Quiz - Jupyter Notebook
Practice Quiz - RStudio IDE
Graded Quiz
IBM Tools for Data Science
What is IBM Watson Studio?
Watson Studio Introduction
Creating an Account on IBM Watson Studio
Jupyter Notebook in Watson Studio - Part 1
Jupyter Notebook in Watson Studio - Part 2
Linking GitHub to Watson Studio
Other IBM Tools for Data Science
IBM Watson Knowledge Catalog
Data Refinery
SPSS Modeler Flows in Watson Studio
IBM SPSS Modeler
SPSS Statistics
Model Deployment with Watson Machine Learning
Auto AI in Watson Studio
IBM Watson OpenScale
Practice Quiz - Watson Studio
Practice Quiz - Other IBM Tools
Graded Quiz
Final Assignment: Create and Share Your Jupyter Notebook
IBM Digital Badge
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