Getting Started with Jupyter Notebook 5 and Python from Pluralsight

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

Python serves many different type of developers, so why should all Python developers use the same development tool? This course, Getting Started with Jupyter Notebook 5 and Python, explores Jupyter Notebook, an essential tool for data, prototyping, and learning that belongs in every Python developer’s toolbox. First, you'll explore the foundations of Jupyter Notebook, including installation and interface navigation. Next, you’ll learn how to go beyond the code and supplement notebooks with rich content such as markdown, visualizations, and data formatting. Finally, you’ll see how to make interactive UIs that communicate, and how to make your ideas available to others. By the end of this course, you’ll have the skills necessary to assemble Jupyter notebooks that can help tell your Python story to others, and help you understand the Python stories of your colleagues.

What's inside

Syllabus

Course Overview

Installing Jupyter Notebook

Moving from the REPL to a Notebook

Leveraging Special Notebook Features

Displaying Rich Content

Extending the Notebook User Interface

Collaborating on Notebooks

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores Jupyter Notebook which has become standard in Python development

Taught by Douglas Starnes, who are recognized for their Python expertise

Develops skills needed for data analysis, prototyping, and learning in Python

Provides foundational knowledge of Jupyter Notebook, including set-up and navigation

Teaches how to use rich content, such as markdown, visualizations, and data formatting, within notebooks

Shows how to develop interactive UIs within Jupyter Notebooks

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Getting Started with Jupyter Notebook 5 and Python with these activities:

Review Python Syntax and Data Structures

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Reinforce your Python skills to establish a strong foundation before beginning the course.

Browse courses on Python Syntax

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Review data types, variables, and operators.
Practice writing basic Python expressions and statements.
Revisit common data structures such as lists, dictionaries, and sets.

Solve Jupyter Notebook Challenges

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Test your skills by solving coding challenges related to Jupyter Notebook.

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Find online platforms or resources that provide Jupyter Notebook challenges.
Choose a challenge that aligns with your current skill level.
Attempt to solve the challenge independently.
Review solutions and identify areas for improvement.

Attend a Jupyter Notebook Workshop

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Immerse yourself in a hands-on environment and learn advanced techniques.

Browse courses on Data Science Tools

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Research and identify upcoming Jupyter Notebook workshops.
Register for a workshop that aligns with your interests.
Attend the workshop, actively participate, and take notes.
Implement the skills and knowledge gained in your own projects.

One other activity

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Participate in a Jupyter Notebook Hackathon

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Challenge yourself and showcase your abilities in a competitive environment.

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Identify Jupyter Notebook hackathons or competitions that fit your skill level.
Form a team or work individually on a project.
Develop a creative and innovative solution using Jupyter Notebook.
Present your project to judges and receive feedback.

Career center

Learners who complete Getting Started with Jupyter Notebook 5 and Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use a variety of tools and techniques to collect, clean, and analyze data, then derive insights from it. They may use Jupyter Notebook to create interactive dashboards, visualize their findings, and communicate their findings through clear and persuasive reports and data visualizations. This course provides a foundational understanding of Jupyter Notebook to help you succeed in this role.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. Jupyter Notebook is a tool they use throughout this process, from prototyping models to deploying them to production. This course will help you understand the basics of Jupyter Notebook to help you succeed in this role.

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Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that supports data analysis and machine learning. They use Jupyter Notebook for data preparation, data transformation, and data analysis. This course provides a foundational understanding of Jupyter Notebook to help you succeed in this role.

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Data Scientist

Data Scientists use a variety of tools and techniques to collect, clean, analyze, and visualize data. Jupyter Notebook is a valuable tool for them because it allows them to quickly and easily prototype new ideas and share their findings with others. This course will help you build a strong foundation with Jupyter Notebook to help you succeed in this role.

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Quantitative Analyst

Quantitative Analysts provide quantitative support to investment bankers, traders, and portfolio managers. They use Jupyter Notebook to analyze large datasets, build models, and create visualizations. This course will help you build a strong foundation with Jupyter Notebook to help you succeed in this role.

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Software Engineer

Software Engineers use Jupyter Notebook for prototyping, testing, and documenting their code. This course will help you understand the basics of Jupyter Notebook, which can be useful when working on projects that involve data analysis or machine learning.

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Research Scientist

Research Scientists use Jupyter Notebook to analyze data and create visualizations for their research. This course can help you learn the basics of Jupyter Notebook, which may be useful in your research.

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Technical Writer

Technical Writers use Jupyter Notebook to create interactive tutorials and documentation. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Data Journalist

Data Journalists use Jupyter Notebook to analyze data and create visualizations for their stories. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Biostatistician

Biostatisticians use Jupyter Notebook to analyze data and create visualizations for their research. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Project Manager

Project Managers use Jupyter Notebook to track the progress of their projects and communicate with their team. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Business Analyst

Business Analysts use Jupyter Notebook to analyze data and create visualizations for their clients. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Product Manager

Product Managers use Jupyter Notebook to analyze data and create visualizations for their products. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Marketer

Marketers use Jupyter Notebook to analyze data and create visualizations for their marketing campaigns. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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Consultant

Consultants use Jupyter Notebook to analyze data and create visualizations for their clients. This course can help you learn the basics of Jupyter Notebook, which may be useful in your role.

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