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  1. Courses
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  3. Introduction to Jupyter Notebooks

Introduction to Jupyter Notebooks

This is an introductory course for absolute beginners who want to start with the Jupyter notebook as a tool.

Theodore Petrou
Theodore Petrou
Data Science | intermediate | 1 hour |   Published: Sep 2022
In partnership with:  Coursera

    Discussions

Overview

1.6KSTUDENTS*
95.7%RECOMMEND*

This course includes:

  • 1 hour of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online
This is an introductory course for absolute beginners who want to start with the Jupyter notebook as a tool.   Who needs Jupyter Notebook? 
  1. If you want a highly lucrative career in machine learning, data science, deep learning, or any other data-driven technologies, you should know how to work with Jupyter Notebook: one of the most important tools a machine learning engineer or a data scientist needs in her (his) day-to-day job!
  2. Jupyter Notebook is also used among scientific communities and mathematicians.
  3. If you are a Python or R developer, looking for a tool to quickly run the ad-hoc scripts, see the result then and there, and fix your code as you go, Jupyter Notebook is the tool you need.
Advantages of Jupyter Notebook:   It is similar to a physical notebook you carry to take notes, in the sense that - you can write textual content, embed images, videos, and run all the code and programs, see the results of your programs - all within the notebook itself. Jupyter notebook supports more than 40 programming languages.  If you are learning Python, Julia, or R, it's highly recommended you start using Jupyter Notebook - you'll love it! 

Skills You Will Gain

Data Analysis
Julia
Jupyter
Jupyter Notebook
Python

Learning Outcomes (At the end of this program you will be able to)

  • Understanding what the Jupyter Notebook is basically 
  • The interface of the Jupyter Notebook 
  • The basics of Jupyter Notebook like Commands, dashboards, etc. 
  • How to install Jupyter Notebook 
  • The Key features of the Jupyter Notebook 

Prerequisites

  • Basic Python programming skills 

Who Should Attend

  • Python Programmers and Developers 
  • Students interested in learning Jupyter Notebooks 

Curriculum

Instructors

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 1: Introduction
2Module 2: Working with Edit and Command Modes:
3Module 4: Advanced Features and Closing:
Theodore Petrou

Theodore Petrou

Theodore Petrou is the founder of Dunder Data and a leading educator in the fields of data science and machine learning. With a deep passion for teaching and a strong command of Python programming, he has authored several influential books, including Master Data Analysis with Python, Master Machine Learning with Python, Master the Fundamentals of Python, and the popular Pandas Cookbook. Through Dunder Data, Theodore has delivered customized corporate training to renowned organizations such as Microsoft, NASA, and the Federal Reserve, equipping thousands of professionals with practical, hands-on expertise.

With a rich background that bridges both industry and academia, Theodore brings a wealth of experience to his teaching. His career has included roles as a Quantitative Developer, Lead Data Scientist, and Credit Risk Professional, where he solved complex problems in predictive modeling, financial analytics, and data strategy. Alongside developing innovative technical solutions, he has devoted much of his career to mentorship and education, fostering a deep and lasting understanding of data science principles.

Theodore’s teaching extends beyond corporate settings into the broader educational community through live courses and workshops. Known for his clear, engaging style, he breaks down sophisticated concepts in Python and data science to make them accessible and actionable for learners of all levels. His mission is to guide aspiring and experienced professionals alike through the intricacies of data analysis and machine learning with clarity, enthusiasm, and real-world relevance.

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Segment 10 - Markdown Basics

Segment 11 - Exiting the Browser Tab

Segment 12 - Completing Exercises

Segment 13 - Creating New Notebooks

Segment 14 - Jupyter Notebook Summary

Segment 15 - Jupyter Notebook Extensions

Segment 16 - Using your Mouse and the Dropdown Menus

Segment 17 - Shutting Down Jupyter

Segment 1 - Launching the Notebook

Segment 2 - Navigating the File System View

Segment 3 - Opening the Notebook

Segment 4 - Jupyter Notebook Basics

Resources

Segment 5 - Edit vs Command Mode

Segment 6- Changing Between Edit and Command Mode

Segment 7 - Changing Modes in a Markdown Cell

Segment 8 - Command Mode Keyboard Shortcuts

Segment 9 - Other Notebook Tips