# Learn to use Jupyter Notebook to create Interactive Computational Stories

Jupyter notebook is excellent for beginners and even better for experienced programmers as it supports more than 40 programming languages, primarily focused on Python.

In this guide, we’re going to explore several popular courses for beginners to learn Jupyter Notebook for Data Science, offered by some of the top educators.

It is an open-source application that is widely used for data analysis work, allowing users to write code in a web browser.

Jupyter Notebook has been widely used by Data Scientists and researchers for writing the code that tells a story.

It’s also affectionately known as the ‘Notebook’ among the Data Science and Machine Learning Enthusiasts.

Juypter Notebook is heavily used for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

So equipping yourself with the Jupyter Notebook skills for data science means that you’re well on your way to entering the world of data science.

And our aim in this brief article is that you’re able to pick the right course to gain the skills from this post.

So let’s dive in…

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## Best Courses to Learn Jupyter Notebook for Data Science

We have evaluated the syllabus and attest that these classes will help you to understand the concepts quickly and easily with illustrations and examples.

### Python and Jupyter Notebooks for beginners

In this course, you will learn Python with Jupyter Notebook from scratch

### Basics of Python Programming for Beginners (with Jupyter)

This Python for Beginner's course helps you to understand the basics and gain familiarity with Jupyter Notebook for Data Science.

### Python for the Jupyter Notebook

In this course, you will learn how to program in Python using the Jupyter Notebook

### Jupyter Notebook for Data Science – Tutorial

This tutorial explains how to install, run, and use Jupyter Notebooks for data science, including tips, best practices, and examples.

### Jupyter Notebook for Data Science - Highest Rated

This course will help you to use Jupyter Notebook for data manipulation and visualization

### Writing Functions in Python

This intermediate-level course aims to help learners get involved in the best practices of writing functions using Jupyter Notebook.

### Tools for Data Science – IBM

In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio.

### Beyond Jupyter Notebooks

In this course, you learn to build your own Data science platform with Docker & Python

### Jupyter Notebook - Big Data Visualization Tool

You will be able to learn Data Ingestion in the Jupyter environment an essential requirement for Data Science and Big Data Engineering.

### Create and Share Analytics with Jupyter Notebooks

This course covers the important aspects of working with Jupyter notebooks, including installation and the role of kernels, magic functions, and running shell commands. In addition, the power of cloud-hosted Jupyter notebooks is explored on AWS, Micros...

### Python and Jupyter for Science Crashcourse!

This Jupyter Notebook course offers a really practical approach to building real projects and you will dive right into the practical work!

### Getting Started with Jupyter Notebook and Python

Jupyter Notebook is an interactive computing environment that transcends code, and it has completely disrupted how many Python developers work and think about software development. This course shows how you can let it do the same for you.

### Using Jupyter Notebooks — Real Python

In this step-by-step course, you learn how to get started with the Jupyter Notebook, an open-source web application that you can use to create and share documents that contain live code, equations, visualizations, and text.

### Introducing Jupyter Online Class | LinkedIn Learning

Meet Jupyter, the open-source tool for presenting projects complete with live code and visualizations.

**Closing Note**

It is important to remember that Jupyter Notebook is not suitable for creating applications.

But, it allows users to create and share documents that contain live code, equations, visualizations, and narrative text.

Thanks for making it to the end.

**Your Guide to Data Science**

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