Here you’ll find resources to help you become familiarized with the machine learning world, if you are in the beginning stages of your machine learning journey. For each resource, a link to the website, as well as the time commitment for the resource is provided.

Intro to Machine Learning – Kaggle (3 hours)

A fairly easy course to follow through with no prior knowledge of ML. The best part about it is that it requires a very low time commitment, so it is something that can easily be completed over a weekend. The examples included use the Pandas library, so knowing Pandas can enhance your understanding of the code used

Intermediate Machine Learning – Kaggle (4 hours)

An extension of the “Intro to Machine Learning” course from Kaggle. A useful resource to learn how to preprocess and manipulate datasets with missing values/irregularities. The course also introduces what can be done after the ML model is built (testing, validation), although these concepts are a bit difficult to understand from the written explanations.

Machine Learning – Coursera (60 hours)

This course provides a thorough overview of machine learning concepts, starting from the very basics and going into some more difficult concepts. Each topic comes with assigned readings and quizzes, as well as some programming assignments, which gives you the opportunity to thoroughly understand the material and apply it.