Free Online Jupyter Notebook Courses and Certifications 2024
Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. It is used for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Popular Courses
This course provides a great opportunity for new learners to quickly learn the basics of Jupyter Notebook. It explains the purpose of this web-based notebook programming environment and demonstrates how to write and manage code in it. Learners will gain an understanding of the fundamentals of Jupyter Notebook and be able to use it to write and manage code. With this course, learners will be able to quickly get up to speed with the basics of Jupyter Notebook and be able to use it to their advantage.
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This Jupyter Notebook Tutorial Python Training course from Quantra provides an introduction to the powerful Jupyter Notebook. Participants will learn how to use the Jupyter Notebook to write and execute Python code, debug code, create and share documents, and create interactive visualizations. By the end of the course, users will have a better understanding of how to use the Jupyter Notebook to write and execute Python code, as well as how to create and share documents that contain live code, equations, visualizations, and narrative text. Click this course to learn how to use the Jupyter Notebook to its fullest potential.
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This Jupyter Notebook for All Complete Jupyter Notebook for Data Science Big Course is perfect for anyone looking to gain an in-depth understanding of the Jupyter Notebook system. Learners will explore the various versions and packages compatible with the Notebook system, master interactive widgets, namespaces, and working with Jupyter in multiuser mode. They will also use Jupyter with a big dataset and apply all the functionalities learned throughout the course. This course is ideal for data scientists, data analysts, data engineers, mathematicians, statisticians, scientists, engineers, image processing and computer vision professionals, machine learning and AI professionals, bioinformatics and biostatistics professionals, programmers and developers, students, job seekers, and anyone wanting to learn new stuff. Click now to get started!
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This course is perfect for new learners who want to get started with Jupyter Notebooks. David provides an introduction to the basics of Jupyter Notebooks and the advantages they offer. Learners can get started for free on IBM Cloud and subscribe to see more videos like this in the future. With this course, learners can easily learn the basics of Jupyter Notebooks and take advantage of the powerful features they offer. So don't wait, click the course and get started today!
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This course provides a great opportunity for new learners to learn how to use Jupyter Notebook Server with AWS EC2 and AWS VPC. It will guide learners through the process of preparing a AWS Virtual Private Cloud, Subnets, Internet Gateways, Route Tables, and more. After configuring the EC2 instance, learners will be taught how to configure nginx, supervisor, and Jupyter so that it can be run automatically on a public IP address. This course is perfect for those who want to learn how to use Jupyter Notebook Server with AWS EC2 and AWS VPC. Sign up now and start learning!
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This course provides a comprehensive introduction to the powerful Jupyter Notebook environment. It is designed to equip learners with the necessary knowledge and skills to effectively leverage Jupyter Notebook for data analysis, visualization, and interactive computing. Learners will learn how to create, edit, and organize Jupyter Notebook documents, execute and document code, use Replit, Google Colab, and Anaconda Distribution, and the basics of Markdown. By the end of this course, learners will have a solid foundation in Jupyter Notebook, enabling them to explore, analyze, visualize data, create interactive presentations, and collaborate effectively with others. Click now to learn Jupyter Notebooks for Beginners!
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This course is perfect for new learners who want to learn how to create a Python Jupyter Notebook Server with Docker and Heroku. It provides step-by-step instructions on how to deploy an interactive notebook, allowing projects to be more literal and easier for non-technicals to run code. It also covers the use of Docker to give control over the application's OS environment, and how to deploy the project to Heroku. Additionally, it explains the caveat that Jupyter notebooks will disappear as soon as a new version is deployed, due to the ephemeral nature of containers. With this course, you will be able to create a Python Jupyter Notebook Server with Docker and Heroku, and gain control over the application's OS environment. Click now to start your journey!
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This course is perfect for all Python developers who want to learn more about Jupyter Notebook. It covers the basics of Anaconda and Jupyter Notebook, as well as more advanced topics such as Menu tabs, Cell types, Modes, Shortcuts, and Magic Commands. Learners will also learn how to publish their Jupyter Notebook files on a website or blog and how to share them with other team members. Whether you are a beginner or an experienced developer, this course will provide you with a comprehensive overview of Jupyter Notebook. Don't miss out on this great opportunity to expand your knowledge!
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This course is perfect for those looking to become familiar with Jupyter Notebook and its features to perform data science tasks in Python. Led by Dražen Lucanin, a developer, data analyst, and founder of Punk Rock Dev, learners will start from basic data analysis tasks and work their way up to learn common scientific Python tools. Through the course, learners will work with real datasets, such as crime and traffic accidents in New York City, to explore data scraping and cleaning. By the end, learners will be able to create insightful visualizations and interactive reports to extract useful information from datasets. Don't miss out on this opportunity to learn the fundamentals of data science with Jupyter Notebook!
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This course is perfect for absolute beginners who want to learn about Jupyter Notebook, a powerful tool used by machine learning engineers, data scientists, mathematicians, and Python and R developers. Learners will gain an understanding of the advantages of using Jupyter Notebook, such as its ability to support more than 40 programming languages, its similarity to a physical notebook, and its ability to share and distribute notebooks. Additionally, learners will gain the skills necessary to use Jupyter Notebook in their own projects. With this course, you will be able to take advantage of the powerful features of Jupyter Notebook and use it to create amazing projects.
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This course is perfect for coders, SaberMetricians, and baseball fans who want to gain insight into the MoneyBall phenomenon and the next wave of player development. Through the use of Python, learners will be able to wrangle MLB PitchF/x data from Clayton Kershaw's 2014 no-hitter and graph the pitches with MatPlotLib and PyPlot. Along the way, learners will also learn best practices for Jupyter Notebook, Python coding, XML parsing, and more. This course provides new learners with an introduction to SaberMetrics, the empirical study of baseball statistics. Don't miss out on this opportunity to explore the world of SaberMetrics and MoneyBall!
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This Learning Path is designed to help new learners understand the Jupyter Notebook, an open-source web application that supports more than 40 programming languages. Dan Toomey, a 20+ year veteran of application development, will guide learners through the process of integrating the Jupyter system with different programming languages, such as R, Python, JavaScript, and Julia. Learners will also learn how to use interactive widgets, namespaces, and work with Jupyter in the multiuser mode. By the end of the course, learners will be able to write code, compute mathematical formulae, create graphics, and view the output, all in a single document and web browser. Click this course to learn how to use Jupyter Notebook and access Big Data with ease!
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This course provides a comprehensive introduction to the Jupyter Notebook, from installation and setup to mastering the core concepts and operations. Through practical examples, learners will gain an understanding of the Jupyter Notebook from beginner to expert level. Topics include creating and running .py files, formatting text, creating tables and equations, embedding images, audios, and videos, changing themes, using shortcuts, installing packages, creating basic and interactive plotting, and more. Click now to learn how to use the Jupyter Notebook quickly and easily!
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This course provides a comprehensive introduction to Jupyter Notebook, a popular open-source web application used by data scientists, analysts, and researchers. Learners will learn how to install and set up Jupyter Notebook, create and execute code cells in Python, and perform data manipulation and analysis using popular Python libraries. They will also learn how to collaborate with others by sharing and exporting notebooks. By the end of the course, learners will have a solid understanding of Jupyter Notebook and be able to use it to perform basic data science tasks. Join this course to get started with Jupyter Notebook and become a data science expert!
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This Data Analysis Crash Course For Beginners (Pandas + Python) is the perfect way to get started with Data Analysis. Learners will gain a comprehensive understanding of the fundamentals of Data Analysis with Python and Pandas library. Through this course, learners will be able to work with Pandas, iPython, Jupyter Notebook, CSV, Excel, TXT, JSON Files and API Responses, and DataFrames (Indexing, Slicing, Adding and Deleting). After completing this course, learners will have a solid foundation in Data Analysis and be ready to explore more in-depth topics in the future.
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This course is designed to teach new learners the fundamentals of data science and real-world computing with Jupyter Notebook. It provides a step-by-step guide to exploring the possibilities in the field of Jupyter, from data exploration to visualization. Learners will learn how to use Jupyter's features to perform various data science tasks, such as data scraping and cleaning, and how to integrate Python 3, R, and Julia with Jupyter for various data science tasks. Take this course to learn how to leverage the power of Jupyter to perform data science tasks efficiently. You will also learn to create insightful visualizations, showing time-stamped and spatial data, and master relatively advanced methods in interactive numerical computing, high-performance computing, and data visualization.
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Frequently Asked Questions and Answers
Q1: Is Jupyter a Python IDE?
Jupyter is not an IDE or an IPython UI, as many may believe. I would argue that Jupyter is a development platform, and you can customize your workspace to your liking. It includes a terminal emulator, allowing you to do whatever you desire.
Q2: Is it better to use Jupyter Notebook or Python?
A regular Python script requires reloading the entire dataset each time it is executed, whereas a Jupyter Notebook allows you to run the cell responsible for loading the data once. This enables you to create new cells to work with the data without having to reload it.
Q3: What Jupyter Notebook courses can I find on AZ Class?
On this page, we have collected free or certified 35 Jupyter Notebook online courses from various platforms. The list currently only displays up to 50 items. If you have other needs, please contact us.
Q4: Can I learn Jupyter Notebook for free?
Yes, If you don’t know Jupyter Notebook, we recommend that you try free online courses, some of which offer certification (please refer to the latest list on the webpage as the standard). Wish you a good online learning experience!
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