This video series teaches Python for complete beginners to programming and data science. In this first lesson we learn how to get started using Python with the Kaggle notebook environment.

This is lesson 1 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below:

Python for Data Analysis: Getting Started
https://www.kaggle.com/hamelg/python-for-data-1-getting-started

This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python.

I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself.

This guide uses the Kaggle kernel environment to deliver content, so you do not need to set up a local Python environment to follow along. Instead, you can simply read each lesson in your browser window and if you'd like to run and interact with the code, you can copy and edit the Kaggle notebook for a given lesson to create a personal copy of it that you can alter and run as you see fit. In putting the guide for the Kaggle kernel environment I hope that it becomes more accessible and interactive while simultaneously avoiding problems with incompatibilities across different versions of Python.

If you would like to set up a local Python environment on your computer, you will need to download Python. It is easiest to download the Anaconda Python distribution from Continuum Analytics (https://www.anaconda.com/).

Introduction to Python Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rCYWmH9wIEYEXXaJ4KAi3jc

Link to the Python for Data Analysis written guide page:
https://www.kaggle.com/hamelg/python-for-data-analysis-index .


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