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Python programming in biology and chemistry

Welcome to the Python programming in biology and chemistry course repository! This repository contains exercises, solutions, and notebooks for learning the Python programming language.

Exercises

Inside the exercises directory, you will find a collection of Jupyter notebooks (.ipynb files) covering various topics in Python. Each notebook contains a set of exercises designed to help you practice and solidify your understanding of Python concepts.

Solutions

The solutions directory contains solutions to the exercises provided in the corresponding notebooks in the exercises directory. These solutions are provided to help you check your work and understand different approaches to solving the exercises.

Notebooks

The notebooks directory contains on-the-fly code snippets and examples that have been created during the course to demonstrate concepts and answer questions. These notebooks serve as additional resources to enhance your understanding of Python programming and to recapitulate concepts that were discussed.

How to Use Exercises in Google Colab

You can easily use the exercises in Google Colab by following these simple steps:

  1. Open Google Colab in your web browser: Google Colab.

  2. In the Colab interface, go to File > Open Notebook.

  3. Select the option GitHub and paste the URL of this repository: GitHub Repository.

  4. You will see a list of notebooks available in the repository. Click on the notebook you want to work on.

  5. Once the notebook is opened, you can run the code cells, edit them, and interact with the exercises just like you would in any Jupyter environment.

  6. If you want to save your changes, you can either save the notebook to your Google Drive or download it to your local machine.

Each notebook contains a "Open in Colab" button at the top, making it easy for you to directly open and work with the exercises in Google Colab.

Happy learning!

Contributing

If you find any issues with the exercises, have suggestions for improvements, or want to contribute additional exercises, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Welcome to the Python course repository! This repository contains exercises and solutions for learning Python programming language.

Exercises

Inside the exercises directory, you will find a collection of Jupyter notebooks (.ipynb files) covering various topics in Python. Each notebook contains a set of exercises designed to help you practice and solidify your understanding of Python concepts.

Solutions

The solutions directory contains solutions to the exercises provided in the corresponding notebooks in the exercises directory. These solutions are provided to help you check your work and understand different approaches to solving the exercises.

How to Use Exercises in Google Colab

You can easily use the exercises in Google Colab by following these simple steps:

  1. Open Google Colab in your web browser: Google Colab.

  2. In the Colab interface, go to File > Open Notebook.

  3. Select the option GitHub and paste the URL of this repository: GitHub Repository.

  4. You will see a list of notebooks available in the repository. Click on the notebook you want to work on.

  5. Once the notebook is opened, you can run the code cells, edit them, and interact with the exercises just like you would in any Jupyter environment.

  6. If you want to save your changes, you can either save the notebook to your Google Drive or download it to your local machine.

Each notebook contains a "Open in Colab" button at the top, making it easy for you to directly open and work with the exercises in Google Colab.

Happy learning!

Contributing

If you find any issues with the exercises, have suggestions for improvements, or want to contribute additional exercises, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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This is the repository for the "Python Programming in Biology and Chemistry" course

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