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An intro to data science for absolute beginners
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README.md

Workshop: Machine Learning for Beginners

This repository contains the code for the workshop "Machine Learning for Beginners" as presented in various occasions at WHU - Otto Beisheim School of Management, such as the Campus for Supply Chain Management, IdeaLab's IdeaHack, or within many executive education programs.

Prerequisites

To be suitable for total beginners, there are no prerequisites. If you are interested to learn more after this workshop, check out the full-semester course Introduction to Python & Programming.

Installation

To follow this workshop on your own computer, a working installation of Python 3.6 or higher is required.

A popular and beginner friendly way is to install the Anaconda Distribution that not only ships Python but comes pre-packaged with a lot of third-party libraries from the so-called "scientific stack". Just go to the download section and install the latest version (i.e., 2019-10 with Python 3.7 at the time of this writing) for your operating system.

Then, among others, you will find an entry "Jupyter Notebook" in your start menu. Click on it and a new tab in your web browser will open where you can switch between folders as you could in your computer's default file browser.

To download the course's materials as a ZIP file, click on the green "Clone or download" button on the top right on this website. Then, unpack the ZIP file into a folder of your choosing (ideally somewhere within your personal user folder so that the files show up right away).

About the Author

Alexander Hess is a PhD student at the Chair of Logistics Management at the WHU - Otto Beisheim School of Management where he conducts research on urban delivery platforms and teaches an introductory course on Python (cf., Fall Term 2019, Spring Term 2020).

Connect him on LinkedIn.