Anaconda and Jupyter are two popular tools in the world of data science and machine learning.

 (data science, machine learning applications, large-scale data processing, predictive analytics, etc.). and comes pre-packaged with many useful libraries for data science.

Jupyter (formerly known as IPython) is a web-based interactive development environment for creating notebook documents. It supports multiple programming languages like Python, R, and Julia. It is widely used in fields like data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

You can use Jupyter Notebooks through Anaconda in the following way:

1. Launch Anaconda Navigator: After installation, you can launch Anaconda Navigator, which is a desktop graphical user interface included in Anaconda that allows you to launch applications and manage conda packages, environments, and channels without using command-line commands.
2. Start Jupyter Notebook: You can launch Jupyter Notebook directly from Anaconda Navigator. After you click the launch button under Jupyter Notebook, it will open in your default web browser.
3. Create a new Jupyter Notebook: Once Jupyter Notebook clicking on “New” and selecting “Python 3” or the kernel of your choice.
4. You’re now ready to write code in the cells of your Jupyter Notebook!
5. To run the code in a cell, you can use the keyboard shortcut “Shift+Enter”.

Remember to save your work often. Jupyter Notebooks have an auto-save feature, but it’s still a good practice to manually save, especially after making significant changes.

The combination of Anaconda and Jupyter is very powerful and is widely used in data science and related fields.