do you try to get started on data science or web project which uses Python? these videos are here to help show you the foundations necessary to walk through a tutorial or other quick start.
We do assume you are familiar with another programming language, and some core programming concepts. For example, we highlight the syntax for boolean expressions and creating classes, but we don't dig into what a boolean is or object oriented design. We show you how to perform the tasks you're familiar with in other languages in Python.
What you'll learn
- The basics of Python
- Common syntax
- Popular packages
Prerequisites
- Light experience with another programming language, such as JavaScript, Java or C#
- An understanding of Git
Courses
Getting started
Python for beginners is the perfect starting location for getting started. No Python experience is required! We'll show you how to set up Visual Studio Code as your code editor, and start creating Python code. You'll see how to manage create, structure and run your code, how to manage packages, and even make REST calls.
Dig a little deeper
More Python for beginners
digs deeper into Python syntax. You'll explore how to create classes
and mixins in Python, how to work with the file system, and introduce async/await. This is the perfect next step if you're looking to see a bit more of what Python can do.
Peek at data science tools
Even more Python for beginners is a practical exploration of a couple of the most common packages and tools you'll use when working with data and machine learning. While we won't dig into why you choose particular machine learning models (that's another course), you will get hands-on with Jupyter Notebooks, and create and test models using scikit-learn and pandas.
Next steps
As the goal of these courses is to help get you up to speed on Python so you can work through a quick start. The next step after completing the videos is to follow a tutorial! Here are a few of our favorites:
- Quickstart: Detect faces in an image using the Face REST API and Python
- Quickstart: Analyze a local image using the Computer Vision REST API and Python
- Quickstart: Using the Python REST API to call the Text Analytics Cognitive Service
- Tutorial: Build a Flask app with Azure Cognitive Services
- Flask tutorial in Visual Studio Code
- Django tutorial in Visual Studio Code
- Predict flight delays by creating a machine learning model in Python
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
from https://github.com/microsoft/c9-python-getting-started
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