Participating in competitions in data science is the most effective method to test your abilities and improve your knowledge. This is why in this article; I’ll discuss the top 9 Data Science competitions that will enable you to explore real-world data and enhance your skills in data science. The mere knowledge of theories is not enough to make a mark in data science. You must put the theoretical knowledge you have acquired into your daily life. In this regard, competitions in data science are the most effective. They offer a variety of advantages.
To help you make life easier, we’ve created an eight-point list of our top competitions. Participation in these events will increase your confidence, skills and data science expertise. If you’re looking to understand concepts in data science, take a look at this Data Science Course program.
Top Data Science Contests
1. Kaggle
Kaggle contests aren’t really about winning money. They’re about doing extraordinary things, working with awesome people and learning many things. It’s very inspiring; I have to say. And completely truthful, even if you’re not able to make it to the very top.
By participating in these thrilling contests, aspiring data scientists can improve their skills while making new connections and learning.
2. Driven data
The competitions for data offered by DrivenData usually last between two and three months. They offer a worldwide community of data scientists that compete in creating the best mathematical model to solve complex prescriptive problems. The competitions held by DrivenData help data scientists design cutting-edge solutions to data science and provide support to nonprofits governments, NGOs and other social impact organizations. DrivenData is a non-profit organization with a dual mission. It aims to assist data scientists in developing their skills and developing new skills and provide support for humanitarian causes.
3. Codalab
CodaLab is an open-source software platform that offers an environment for conducting computational research in an efficient and reproducible method. Two services are offered by CodaLab provides:
i. Allowing companies to capture complicated processes of research in a reproducible manner.
ii. The data scientist can participate in an event to help solve problems that businesses have.
4. Iron Viz
Iron Viz is the world’s biggest competition for data visualization held by one of the most renowned companies in the industry: Tableau. The competition consists of a month-long qualification phase then a championship round for the top three finalists. The only requirement that participants must meet is participating in the access Tableau Desktop. Tableau Desktop Public Edition, an unpaid version of the software, is available.
5. Topcoder
Topcoder is like Coda Lab in that it is also a collaborative effort to collect codes and perform research. They offer a range of competitions and challenges on their main website, ranging from data science web design. Many of them have decent prizes, but some fulfill an opportunity.
All through all of the time, TopCoder also hosts regional tournaments that aren’t the same size as TopCoder Open. However, they still permit a wide range of participants to participate and build their skills. The best participants are invited to the free trip of a week to the finals held on the site in which they are able to compete for cash prizes and gain knowledge from each other.
6. International Data Analysis Olympiad
The International Data Analysis Olympiad is an annual competition in data science held by Yandex, the Higher School of Economics and Yandex.
The competition is open to all regardless of whether they are groups or individuals or postgraduate, undergraduate, and PhD. Students, corporate employees, as well as researchers or data scientists.
Each competition is broken down into two sections. The first is online, where all teams compete to make it into the next round. The second portion is limited to the top 30 teams from the initial round. It is generally held offline in a particular area, usually at the Yandex office in Moscow. The most valuable prizes are typically awarded to the top teams.
7. CrowdANALYTIX Community
CrowdANALYTIX is an open-source analytics platform that offers competitions for data modelling exploring machine learning, deep learning, artificial intelligence and natural processing of languages. These challenges aren’t strict like other ones.
These contests are a little different and are considered more of a work-in-progress development for continuous iteration. The platform is composed of two “layers,” the machine layer of bots and then the humans who build these algorithms and bots. The top algorithms are then transferred into CrowdANALYTIX’s database and checked for refinement. If the algorithm begins to lose its effectiveness, it’s returned to the community, where it can be tweaked or rebuilt.
8. Bitgrit
Bitgrit is a brand-new contest platform for data scientists, launched at the end of August 2017 by Japanese company Bitgrit Inc. It is home to more than 25,000 data scientists across the world.
Bitgrit is an online platform that allows data scientists to join an international community and network. Bitgrit’s competition system aims to tackle the problems of businesses effectively using the expertise of the masses. Other services offered by Bitgrit include AI consulting and data visualization, such as the COVID tracking tool.
9. Machine Hack
Machine Hack is an online platform on which you will find a variety of machine learning competitions where you can participate in the test and test your ML abilities.
Machine Hack also has a community contributor section with thousands of Data Scientists and Machine Learning Developers who provide their stories and tips, tutorials and more.
Conclusion
These hackathons and contests can be a great way to increase your knowledge. It is possible to think of them as a set of training wheels to prepare you for dealing with data and finding the most effective solutions for data science. Therefore, it is crucial to participate in these contests and not be concerned about winning or losing. Even if you don’t win, however, you’ll gain a lot of knowledge, and that’s a win-win.
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