Jupyter Notebook Basics

About this course

With Jupyter Notebook, you can create and share integrated documents containing live code, equations, and visualizations to share stories with data. In this course, you will be introduced to Jupyter Notebooks and the typical workflow for documenting, visualizing, and executing Python scripts and datasets. You’ll also learn some best practices and caveats in managing notebooks. Finally, you’ll get an overview of Anaconda Cloud features, and become familiar with how to run a notebook on your system locally.

What you'll learn—and how you can apply it

By the end of this hands-on course, you’ll understand:

When to use/not use Jupyter Notebooks
The basics of Markdown and math LaTeX
The workflow and best practices for effective notebooks

And you’ll be able to:

Tell better stories around your data with clear documentation
Integrate context, visuals, and resources around your Python code
Avoid common pitfalls when using notebooks

This training is for you because…

You are a budding data science professional wanting to tell stories with data and Python.
You are a software engineer who wants a better tool to visualize outputs and data from code.
You lead a data team and want a more integrated and interactive documentation solution for code modules.

Prerequisites

Basic understanding of Anaconda distribution
Basic understanding of Python

Recommended preparation

Get Started with Anaconda on-demand course
Introduction to Python Programming learning path

Setup

To open Anaconda Notebooks:

Go to Anaconda Notebooks
Click on 'Sign Up' or 'Sign In' if you already have an account from the top navigation menu
Click 'Launch Notebook'

About the Instructor

Thomas Nield is the founder of Nield Consulting Group and Yawman Flight, as well as an instructor at University of Southern California. He enjoys making technical content relatable and relevant to those unfamiliar or intimidated by it. Thomas regularly teaches classes on data analysis, machine learning, mathematical optimization, and practical artificial intelligence. At USC, he teaches AI System Safety, developing systematic approaches for identifying AI-related hazards in aviation and ground vehicles. He's authored three books, including Essential Math for Data Science (O’Reilly) and Getting Started with SQL (O'Reilly).

He is also the founder and inventor of Yawman Flight, a company developing universal handheld flight controls for flight simulation and unmanned aerial vehicles. You can find him on Twitter | LinkedIn | GitHub | YouTube.

Questions? Issues? Contact learning@anaconda.com.

Curriculum01:21:40

Getting Started
Course Overview and Learning Objectives 00:03:29
What is Jupyter Notebook and JupyterLab? 00:08:24
Anaconda Navigator 00:03:52
Exercise: Writing and Documenting Code 00:02:30
Notebook Workflow
Executing Python Code 00:05:55
Rendering Markdown Cells 00:06:33
Working with External Files 00:04:23
Rendering Math LaTeX 00:02:47
Shell and Magic Commands 00:03:40
Exercise: Plot the Function 00:01:33
Using Anaconda Assistant in Notebooks
Using Anaconda Assistant 00:09:24
Exercise: Using Anaconda Assistant 00:02:14
Notebook Debugging and Caveats
Debugging Tools 00:13:28
Where Jupyter Notebooks Fail 00:07:14
Exercise: Find the bug 00:03:56
Conclusion
Summary 00:02:18
End of Course Survey
Course Completion

About this course