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Key Reasons To Join Kaggle as a Beginner in Data Science

Key Reasons To Join Kaggle as a Beginner in Data Science

If you're starting out building your Data Science career and started to learn data science,  you've probably often heard the advice "do start your journey on Kaggle!". This may have put you under confusion about why exactly you should join it. There’s always the thought of “What does Kaggle have for beginners?”,” What is Kaggle?”, “How to get started with Kaggle?”, “How to use Kaggle for beginners?” and many such reasonable questions!

Learning data science can be overwhelming. Finding a community to share code, data, and ideas can also seem like an overwhelming as well as far-fetched task. But there is one spot where all of these characteristics come together. That beautiful place is called Kaggle. And in this blog, we will be going through some key reasons why every beginner in data science shall join Kaggle!

Join Kaggle as a Beginner in Data Science

Before we get started with the Kaggle walkthrough, let’s understand what exactly Kaggle is! Kaggle is an Airbnb for Data Scientists, Data Analysts and all Data enthusiasts, where they spend their nights and weekends. It’s a crowd-sourced platform to attract, nurture, train and challenge data scientists from all around the world to solve data science, machine learning and predictive analytics problems.

It has over 536,000 active members from 194 countries and it receives close to 150,000 submissions per month. It’s a website for sharing ideas, getting inspired, competing against other data scientists, learning new information and coding tricks, as well as seeing various examples of real-world data science applications. Isn’t it amazing? Let’s go through some of the most amazing features which Kaggle has to offer one by one!

Reasons to join Kaggle

1. Kaggle Courses

As a beginner in data science, I was always on the hunt for courses that will provide me with useful resources to learn data science. It’s great to find that Kaggle provides you with useful courses which can boost your data science journey from beginner to expert! There are 16 such courses you can opt for, and the best part is, now you can get a certificate as well after completing each course!

Features of Kaggle

“Kaggle Learn” provides you with a set of 16 micro-courses marketed by Kaggle as “the single fastest way to gain the skills you’ll need to do independent data science projects.” The courses offer some of the best and quickest introductions to the field by giving you a taste of a range of topics. From Python, machine learning, data visualization, SQL, deep learning, natural language processing (NLP) and reinforcement learning, the platform explains these topics splendidly.

2. Code/Notebooks

Codes and Notebooks are plentiful on Kaggle. If you want to see countless examples of code from other Kaggle users, you can easily search Notebooks that include code, as well as text, where most users comment their code nicely. It is a great way to learn, practice, and see how others perform similar problems. You can see several examples that will show end-to-end machine learning models.

So, any problem you run into, you can search for similar approaches and you'll be amazed to see hundreds of different approaches from which you can learn! After all, it's all about learning and sharing. You learn from other notebooks and share your approaches to the community.

Also, most importantly, Kaggle has an amazing ranking system that indeed serves you to display your portfolio which you can build and show the recruiter your progress. The more you contribute your work on Kaggle, with codes, discussion, etc., the more your Tier increases. You start off as a Novice and build your journey towards the above tiers!


3. Datasets

Datasets are not just simple data repositories. Each dataset is a community where you can discuss data, discover public code and techniques, and create your own projects in Notebooks. You can find many different and thousands of interesting datasets of all shapes and sizes if you take the time to look around and find them! You can explore each dataset, explore different approaches from notebooks associated with those datasets, and you can contribute your own dataset to the community!

There are lakhs of datasets freely available, which you can use to enhance and experiment with your data science skills and knowledge. You can choose from a variety of datasets with different use cases such as medical, NLP, Finance and much more for your data science projects.

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4. Community


This is the best part of Kaggle which we admire the most! The community! Like Medium, GitHub, Stack Overflow, and LinkedIn, Kaggle serves as a huge community where data analysts, data scientists, and machine learning engineers can come to learn, grow, and network.

You can post your work (data, code, and notebooks) that can be ultimately shared to grow your own community. Being a part of a community also has its own benefits, because we highly recommend starting on Kaggle to grow your own community and reach out to other communities as well. We make friends through Kaggle, and we learn from each other's approaches. You can also ask your doubts in the community and there will be a lot of people who will be solving your doubts within a day or two! You grow by sharing and connecting with like-minded people, and that's the thing we like the most about Kaggle communities!

5. Competitions

Competitions are the best source to test yourself and see how you rank amongst peers, but most importantly, help people. Kaggle offers countless competitions right from very beginner level competitions to advanced levels. As a beginner, you can always rely on some easy competitions like Titanic survival competitions.

You can learn a plethora of things from this competition, that later you can try with some recent Tabular series competitions which are organized every month by Kaggle itself! There are impressive rewards as well, but as a beginner focus should always be on learning things!


Well, these are the most important reasons why every data science aspirant or a beginner should join Kaggle! So, when are you joining your Kaggle journey?