The different parts of the presentation are in the following files:

1. The Basics.ipynb
2. Beyond the basics.ipynb
3. Use Case - Gmail API.ipynb
4. Use Case - Directory Monitor.ipynb
5. Use Case - Working with AWS.ipynb
6. Use Case - Machine Learning.ipynb

First you need to do one of the following:

• Install Anaconda
• Install the regular Python distribution + pip install jupyter

Then, do the following:

1. Clone this repo

2. Navigate to the root of this repo

3. Run the following command:

    jupyter notebook
   

Python without any special software installed can be downloaded from here. I recommend installing Python 3, if you would like to test any of the examples in this presentation.

Anaconda is a great python distribution which comes with the most used packages for data science. If you would like to use Python for data analysis, machine learning etc., then I recommend installing Anaconda. Anaconda can be installed from here. Again, I recommend the Python 3 version.

If you find a python package that you would like to install, you can use pip (Python Package Index). Pip comes with the default Python installation. To install a package using pip, use the following command:

pip install <package name>

I recommend installing a Python IDE to edit your Python scripts. The one I prefer is PyCharm, which can be downloaded from here. The "Community" edition is more than sufficient for most tasks.

When you have installed PyCharm, you need to set the path to your Python installation. This is can be done after you have created your first project. The path to your Python installation should be set in:

File > Settings > Preferences > Project:<project name> > Project Interpreter