4-Hours Python Quick Start

Goals

• Learn programming basics
• Learn Python basics
• Get some foundations for future technical trainings (e.g. in data science)
• Become a Python expert

Target Audience

People without prior programming experience, but proficient enough to install software such as Conda on their computer.

Approach

It is unfortunately not possible to cover all of Python in full details in just a few hours (most people spend years becoming true experts!). Therefore, this collection of notebook gives an overview of the main concepts, without going into full details. They are concise, and target a quick ramp-up, while still hopefully containing enough information to be self-consistent and readable offline. I encourage you to execute the notebooks as you read them and to solve the little exercises as you go. The best way forward once you are done with the notebooks is probably to work on a little project (I might add some content to this repository in the future).

Why Python?

• In 2021, it is the language of choice for data science and machine learning
• Powerful language; can be used to build anything from quick scripts to full-fledged industrial applications
• Beginner friendly
• Many hi-performance and state-of-the-art libraries for numerical computation and machine learning

Setup

The content for this class is in the form of Jupyter notebooks, in the notebooks/ folder. The course is meant for Python 3 (we recommend using 3.7 or higher).

For running the notebooks, you have mainly two options:

• Running them in the cloud, for instance on Google Colab
• [recommended] Run them on your own machine. For this, you'll need to install Python, Jupyter, as well as numpy, pandas, matplotlib, or, alternatively a distribution such as Anaconda.

How to set this up on your own machine

• Clone or download this repository from GitHub. To do so, click the green "Code" button on the repository GitHub page, and then either git-clone it (if you know how to do that), or simply click "Download ZIP"
• Install Anaconda by following the instructions for your system here
• (Option A) Follow the Anaconda Getting Started guide, and in particular the section named "Run Python in a Jupyter Notebook", which will show you how to run Jupyter notebooks. You will need to launch the Jupyter notebook from the notebooks directory that you downloaded along with this repository.
• (Option B) If your system has a terminal, you can type

cd <path to notebooks directory>
jupyter notebook

Content

Basics

• Introduction
• Jupyter cells & executing code
• Variables
• Types
• Operators
• Calling functions

Data Structures

• Lists
• Tuples
• Sets
• Dicts (hashtables)

Conditionals and Loops

• Conditionals
• Loops

Functions and Classes

• Writing Functions
• Classes
• The Python Standard Library

Some things that are not included...

(in the future I might try to include some of these)

• Error handling and exceptions
• Inheritance
• Generators
• map, reduce and many other built-in functions
• Unit testing
• Decorators
• Dunder methods
• ...

Contact

If you spot any issue, or have improvement suggestions, feel free to contact me: jherzen at Google mail service.