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kickstart-into-programming's Introduction

Think like a computer, talk like a computer

This repo contains material to for people interested in getting started with programming. The objective is to introduce the programming mindset and offer a quick introduction into coding in python.

In this repository we will cover the general concepts needed to get into coding in python. You do not need to install anything on your computer in order to work with the material as we will be using the browser based Google Colaboratory.

Before you start

If you are not familiar with Google Colab, please start with Intro to Colab notebook which shows you how to work with Colab.

Why should you participate in this course?

This course is designed to help build foundational skills and give fundamental knowledge of computer programming. It is to be thought of as a one day stand alone program that will provide a introduction into programming rather than any expert knowledge or skill building.

Who is this course for?

The intended audience of this course is participants in the proTechnicalle program. This means young adults who are interested in learning about MINT/STEM topics.
The assumption is that the audience bring good understanding of high school level math and physics.
Specifically, general knowledge of algebra, formulas and functions combined with good problem solving experience gives a good starting point for all participants to follow course material. Prior experience in coding, programming is not expected. Any prior experience will allow deeper understanding of topics in the course.

What is the expected outcome?

At the end of the course/day, participants will know: What they will learn in future programming courses
What are some potential next steps to go deeper into the topics
There should be no barriers left preventing participants from getting started in programming and coding.

How to Start

Learn the fundamentals of python programming:

Next Steps

Read up on the "correct" way to write python code:

Do an online course

Acknowledgments

Thank you to the data science team at neue fische for publishing the notebooks upon which this material is based (https://github.com/neuefische/ds-welcome-package)

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