How to learn the basics of data science and machine learning for free with Kaggle
By: Rugare Maruzani
Tags: Coding, Kaggle, Data Science, Machine Learning, Beginners Guide

How to learn the basics of data science and machine learning for free with Kaggle

Photo by Alexandru Acea on Unsplash

Kaggle is an online community of data scientists and machine learning users. The website has a focus on sharing and analysing data sets; and offers data analysis and machine learning competitions with cash prizes. One of the most overlooked aspects of Kaggle, though, are the exceptional short courses for beginners to learn the basics of this discipline. Kaggle courses are free and have good balance between teaching the core fundamentals and not overloading users with advanced concepts and information which can be picked up in time. In this short article, I want to show you how you can get started with learning data science and machine learning for free with Kaggle courses.

Sign up

First things first, you will need to sign up to use the website. Kaggle is owned by Google, so if you already use Google services like YouTube or Gmail, then you can use that account to register a Kaggle account. If you don’t have a Google services account, you can sign up using any email account you like.

Screenshots by Rugare Maruzani, author

Courses

Once you’ve signed up and signed into Kaggle, navigate to the Courses section on the left-hand side of the webpage. As a beginner, you’ll want to start with the Python course. I’ve already completed that course so you won’t see it in the image below. Python is the language of choice for machine learning and data science, particularly for beginners. I think you can jump right into this course with no prior coding experience, but Kaggle recommends you get familiar with some absolute basics before starting the course. When you get to the end of each lesson, it’s important you practice what you just learnt by clicking the link in the Your Turn section at the end of each lesson.

Screenshots by Rugare Maruzani, author

After completing the Python course, I would recommend taking on the Pandas course. Pandas is one of the key Python libraries and this course will teach you how to work with Pandas as well as introduce you to how libraries work in Python. Next, I would do the Data Visualisation module followed by Introduction to Machine Learning and Intermediate Machine Learning

Study other people’s Notebooks

One of the great things about Kaggle is the community can share their data science and machine learning work via Notebooks. As a complete beginner these Notebooks can be intimidating and difficult to comprehend, however, the more you read them the more you will understand, and the more patterns you will notice. I would recommend looking for Notebooks in an area you are interested in and study those. You will find Notebooks analysing health, sport, population and disease data among many other topics. You also have the ability to copy Notebooks to your own profile, allowing you to tinker and break the code, which is a fantastic learning technique.

Search for Notebooks by clicking on the Notebooks tab (blue arrow), and you can copy Notebooks and tinker by clicking the Copy and Edit button (red arrow). Screenshots by Rugare Maruzani, author

Conclusion

After going through some Kaggle courses, I think you will have a good idea of whether data science is an area you are truly interested in and want to pursue further. If so, you will have noticed other courses to develop your skills as a data scientists and machine learning practitioner. Don’t forget to collect the certificate you earn after completing a course and sharing it on LinkedIn!