Create and Share Analytics with Jupyter Notebooks from Pluralsight

Python has exploded in popularity in recent years, largely because it makes analyzing and working with data so incredibly simple. Jupyter is an execution environment rather than a fully-fledged IDE, but even so, notebooks have various important features that are worth understanding thoroughly. In this course, Create and Share Analytics with Jupyter Notebooks, you will learn how Jupyter notebooks are a key driver of Python’s popularity, by providing an incredibly intuitive, interactive environment for executing Python programs. First, you will learn how to get up and running with Jupyter notebooks, and how best to leverage features such as markdown to enhance the readability of your code. Next, you will discover how more advanced features such as magic functions work, and how the next generation offering from Jupyter, named JupyterLab goes even further towards a fully-fledged development environment. Finally, you will round out your knowledge by working with cloud-hosted Jupyter notebooks on each of the major cloud platforms. When you’re finished with this course, you will have the skills and knowledge to leverage the full power of Jupyter notebooks and Jupyterlab, particularly in the context of cloud-hosted notebooks for distributed and collaborative use-cases.

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Covers core concepts of Python, including data analysis and visualization, which is a highly relevant skill in many industries

Introduces Jupyter notebooks, an important tool in Python for interactive data analysis and visualization

Provides guidance on using advanced features of Jupyter notebooks, enabling learners to enhance the readability and functionality of their code

Covers JupyterLab, the next-generation platform for Jupyter notebooks, offering a more comprehensive development environment

Includes practical hands-on experience with cloud-hosted Jupyter notebooks on major cloud platforms, preparing learners for real-world applications

Taught by Janani Ravi, an experienced instructor in the field of data analysis and Python, enhancing the credibility of the course

Career center

Learners who complete Create and Share Analytics with Jupyter Notebooks will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use computational and statistical techniques to understand data and create data-driven solutions to complex problems. The course, Create and Share Analytics with Jupyter Notebooks, will help you build a foundation in Python programming and Jupyter notebooks. These skills are essential for Data Scientists, who need to be able to analyze and interpret large datasets. The course will also introduce you to cloud-hosted Jupyter notebooks, which are becoming increasingly popular for distributed and collaborative use-cases. The fit score of 90 indicates that this course is an excellent choice if you want to pursue a career as a Data Scientist.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations and decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 85 indicates that this course is a valuable resource for aspiring Data Analysts.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. They use these models to predict outcomes and make decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you build a foundation in Python programming and Jupyter notebooks. These skills are essential for Machine Learning Engineers, who need to be able to develop and deploy machine learning models. The course will also introduce you to cloud-hosted Jupyter notebooks, which are becoming increasingly popular for distributed and collaborative use-cases. The fit score of 80 indicates that this course is a good option for aspiring Machine Learning Engineers.

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Statistician

Statisticians collect, analyze, and interpret data. They use this information to make predictions and draw conclusions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 75 indicates that this course may be useful for aspiring Statisticians.

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Business Analyst

Business Analysts use data to understand business needs and make recommendations. They work with stakeholders to identify and solve problems. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 70 indicates that this course may be helpful for aspiring Business Analysts.

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Financial Analyst

Financial Analysts use data to evaluate investments and make recommendations. They work with clients to develop financial plans and strategies. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 65 indicates that this course may be helpful for aspiring Financial Analysts.

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Risk Analyst

Risk Analysts use data to identify and assess risks. They work with organizations to develop strategies to mitigate risks. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 60 indicates that this course may be helpful for aspiring Risk Analysts.

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Data Engineer

Data Engineers design and build systems to store and process data. They work with data scientists and other stakeholders to ensure that data is available and accessible. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 55 indicates that this course may be helpful for aspiring Data Engineers.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with users to understand their needs and develop solutions that meet those needs. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to develop software applications. The fit score of 50 indicates that this course may be helpful for aspiring Software Engineers.

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Analyst Programmer

Analyst Programmers use programming skills to analyze data and solve problems. They work with data scientists and other stakeholders to develop and implement solutions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and develop solutions. The fit score of 45 indicates that this course may be helpful for aspiring Analyst Programmers.

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Data Visualization Specialist

Data Visualization Specialists use data visualization tools to create visual representations of data. They work with stakeholders to communicate insights and make data more accessible. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to create data visualizations. The fit score of 40 indicates that this course may be helpful for aspiring Data Visualization Specialists.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. They work with portfolio managers and other stakeholders to make investment decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze financial data. The fit score of 35 indicates that this course may be helpful for aspiring Quantitative Analysts.

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User Experience Researcher

User Experience Researchers use research methods to understand user needs and improve user experiences. They work with designers and other stakeholders to create products and services that are easy to use and enjoyable. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and make recommendations.

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Market Researcher

Market Researchers use research methods to understand consumer behavior and market trends. They work with marketers and other stakeholders to develop and implement marketing strategies. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and make recommendations.

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Information Security Analyst

Information Security Analysts use their knowledge of computers and networks to protect organizations from cyberattacks. They work with security teams and other stakeholders to develop and implement security measures. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and identify security threats.

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