Learn the Basics of Jupyter Notebook, Data Manipulation, Visualization, and Collaboration in Python Environment
What you will learn
Installing and setting up Jupyter Notebook on their computer.
Creating, opening, and saving Jupyter notebooks.
Navigating the Jupyter Notebook interface and working with cells.
Executing Python code in Jupyter Notebook and working with variables.
Using Markdown to format text and create headings, lists, and tables.
Importing external libraries and modules.
Performing basic data manipulation and analysis with Python
Collaborating with others by sharing and exporting notebooks.
Description
Jupyter Notebook is a popular open-source web application that is widely used by data scientists, analysts, and researchers to create and share documents that contain live code, equations, visualizations, and narrative text. It is an interactive data science environment that allows users to explore, manipulate, and visualize data in real-time. Jupyter Notebook is built on top of Python, but it also supports other popular programming languages such as R and Julia.
This short course is designed to provide an introduction to Jupyter Notebook and to help you get started with basic data science tasks using this powerful tool. In this course, you will learn how to install and set up Jupyter Notebook on your computer, create and execute code cells in Python, perform data manipulation and analysis using popular Python libraries.
Installing and Setting up Jupyter Notebook
The course will start by showing you how to install and set up Jupyter Notebook on your computer. You will learn how to create a new notebook, how to add and delete cells, and how to execute code cells. You will also learn how to save and download your notebooks, and how to share them with others.
Data Manipulation and Analysis with Python
In the next section of the course, you will learn how to perform data manipulation and analysis using popular Python libraries. You will learn how to read in data from different sources, how to clean and transform data, and how to perform basic statistical analysis.
Collaboration and Sharing with Jupyter Notebook
Finally, in the last section of the course, you will learn how to collaborate with others by sharing and exporting your notebooks.
Conclusion
By the end of this course, you will have a solid understanding of Jupyter Notebook and be able to use it to perform basic data science tasks. Jupyter Notebook is a powerful tool for data exploration, analysis, and visualization, and it is widely used by data scientists, analysts, and researchers around the world. Whether you are just getting started with data science or you are an experienced data scientist, Jupyter Notebook is a tool that you should have in your toolkit.
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