Introduction to Jupyter Notebooks

By Romeo Radanyi

Leveraging Jupyter Notebooks for data analytics and visualization.

3 hours
  • 25 Lessons
  • 1 Course Quiz

About the course

There is so much data out there, just waiting to be analyzed, but have you ever wondered how much easier it could be to interpret if you just had a way to visualize these datasets in an interactive way? If only there was a tool that could help us import a data set, transform it, perform calculations, analyze and visualize it, then document these processes and steps along the way so it can be shared with others. Well, that is exactly what Jupyter Notebook will allow you to do.

In this course, you’ll learn:

  • How to set up and use Jupyter Notebooks.
  • What data analytics and visualization is, its importance and how it can be harnessed.
  • How to take a real dataset and turn it into charts, graphs, interactive elements, predictions, etc.
  • How to start leveraging Machine Learning techniques to get even more from your data.
  • How to harness cloud service providers like AWS, Google, Azure’s hosted notebook services in your data science and machine learning lifecycles

This course is made for beginners, so if you don’t know anything about data science or machine learning but you’re interested in getting started, you are definitely in the right place. Some Python experience is beneficial but not necessarily required. If you can understand basic coding, you will get along just fine.
Come along and learn all about data science, machine learning, and how to do all kinds of amazing things that look and sound like magic to most developers!

What you will need

  • Basic Python programming skills

What you can expect

  • Read, write, and interact with Jupyter Notebooks in Python.

  • Use Python and other libraries to input, transform, calculate, graph, and visualize a data set with.

  • Learn where and how to find interesting datasets for future data science and machine learning projects.

  • Learn how to use Jupyter on different cloud service providers like AWS, Google and Azure.

  • Create an isolated, easy to maintain data science workbench on both Windows or Mac OSX.

Practice alongside courses in Cloud Playground

What is Cloud Playground? Cloud Playground lets you build skills in real-world AWS, Google Cloud, and Azure environments. Spin up risk-free Sandboxes, Servers and Terminals and follow along with courses, test a new idea or prepare for exams.

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Who’s going to be learning?

How many seats do you need?

  • $499 USD per seat per year
  • Billed Annually
  • Renews in 12 months

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