How To Take Micro-Courses With Kaggle Learn

Kaggle Learn is one of the most popular online platforms for competitions in Data Science. If you are a beginner however, it can be quite intimidating, but that's why we are here to help you get started on this learning app.

There are some listed competitions on the app that have prizes of more than $1,000,000, which is quite enticing. Some of the top teams boast of having decades where they combined some of their great experience of tacking the problems and analyzing satellite data.

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It is, therefore, no surprise that most people love to get started on Kaggle. They, however, wonder how this can be done, whom they will be up against, and whether or not it is worth their time. We're going to tell you all you need to know up next.

How To Take Micro-Courses With Kaggle Learn
Image Source: Wikipedia.org

Pick A Programming Language

This is the first step. Pick a language and ensure that you stick to it. Python and R are extremely popular on Kaggle and they cover a broad community of data science. If you are starting on a blank slate, the option would be Python, as it is more general-purpose.

Get To Know The Kaggle Learn Basics

You should at least know how to navigate the site load and plot the data. This also informs all of the various decisions you shall be making throughout the model training. If you decide to use Python, then the Seaborn library is the best option.

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Use Training Models

Before you jump into Kaggle, it is highly recommended that you should use a training model first to make the transition easier. This also allows you to become quite familiar with the libraries and get a lay of the land.

Start Competing To Learn More

Having laid the foundation, it is now time to move on to the featured competitions. Generally, these shall require more time and effort. For this reason, it is recommended that you pick your battles wisely and enter competitions that expose you to technologies and techniques.

How To Take Advantage Of Kaggle Learn

Set goals

If you have ever played an addictive game, then you shall understand what we are talking about. Setting goals helps you move from one level to another, as this is bound to be just as addictive as a video game, especially when you are trying to win.

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Review other winning kernels

Kaggle has an inbuilt cool feature where participants can submit their kernels for others to see. These are short scripts that help explore the concepts and also showcases the techniques used. You can even share them.

When you are starting a competition and you hit s rock, you can view other popular kernels and get some ideas on how to move on.

Ask questions on the Kaggle Learn forums

Never be afraid to ask questions, even those that you think sound stupid. Really, what's the worst thing that can happen? Nothing. You could be ignored, or you could end up with an answer to your questions, so go ahead and ask.

Work alone for a while

This is a great idea so you can develop your skill. It will also force you to tackle each step of the machining process, including data cleaning, exploratory, model training, and feature engineering.

Team up with others

Teaming up can help you push your boundaries and learn more. Most of the past winners are still there and in teams. They have joined forces to combine their knowledge. Additionally, when you master the skills, you can be able to collaborate with others who have more knowledge.

Remember that this is just a stepping stone

You shouldn't necessarily commit yourself to be a long-term Kaggler. In case you do not like the format, that's no problem, most people use it as a pathway to moving on to better projects.

Don't get caught up with rankings

Most beginners start to worry when they are in the low ranks, which show up on their profiles. Of course, in competition, they have to be ranked, and this is really not a big deal. No one is going to judge you since you are a beginner and with time you will rise.

How To Take Micro-Courses With Kaggle Learn
Image Source: Wikipedia.org

Kaggle Learn Conclusion

So, if you have been having questions about Kaggle, we hope that we have answered them for you. The most important thing to note is that you shouldn't take it too seriously, and take as much time as possible to learn the basics so you can master it all.