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5 Popular Hackathon Platforms Data Scientists Should Know About

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5 Popular Hackathon Platforms Data Scientists Should Know About

Key takeaways

  • Hackathons are an effective hiring tool for companies seeking machine learning and data science talent.
  • They offer tech enthusiasts and beginners a chance to gain practical experience and improve their skills.
  • The article highlights popular online hackathon platforms that cater to a global audience.
  • MachineHack is one notable platform that provides a structured environment for participants to tackle real-world problems.

Takeaways drafted with AI from the article text.

Hackathons have become a new and efficient way of hiring professionals in areas of machine learning, AI and data science, especially for talent-starved mid-sized to smaller companies. Since the practical know-how of various tools and techniques matters during the hiring stage, hackathons have become a perfect way to zero down on the ideal candidate with a mix of data science and programming skills.   Hackathons are also a go-to solution for tech enthusiasts and beginners keen on learning new skills and scoring hands-on experience in real-life business scenarios and develop both programming and problem-solving skills. It is also a good way to know the latest trends in the IT community. In this article, we list down popular machine learning hackathon platforms which boast a formidable user base of machine learning enthusiasts, interesting datasets and problem statements. We compiled platforms that conduct online hackathons so that anyone from across the globe can participate. (The list is in no particular order).

MachineHack:

The hackathon platform by Analytics India Magazine is an online platform that hosts engaging hackathons for ML enthusiasts. It enables data science professionals to elevate their skills to newer heights. Participants can compete on various real-world problems, and find solutions using tools in machine learning and data science. Participate can sign up for free. Participants are given a detailed overview of the problem statement, along with other details such as background, prizes, evaluation, criteria, duration of hackathon, levels etc. The results are compared to that of other participants and scores are included in the leaderboard. The hackathons are designed by the in-house data science team. New hackathons are added every 2-3 months. Participate here.

TechGig:

A leading online tech community to learn and update skills, TechGig hosts several hackathons for machine learning and data science enthusiasts. From basic coding to Java, it hosts hackathons from various companies that lets participants learn, practice and compete with the best in the industry. This platform essentially hosts sponsored hackathons from top IT companies that can give an exposure to participants to both win lucrative prizes or a chance to get recruited at leading data science companies . Participate here.

Hackerearth:

This another popular online platform is for educational purpose mostly. It focuses on improving skills in machine learning and data science. They have sponsored machine learning hackathons based on challenges from different industry verticals, giving an exposure to machine learning problems to the participants. The competitive ML challenges are conducted by leading companies to test the skills in deep learning and data science with an intention to hire, outsourcing for a project or simply rewarding them with prizes. Participate here.

Kaggle:

One of the most popular ML hackathon platforms and the first ever to build a platform for hackathons, Kaggle brought hackathons to the forefront and shaped it as an ideal platform for finding and recruiting exceptional talent. Kaggle regularly conducts online hackathons for tech enthusiasts from across the world. The problem statement ranges from machine learning to deep learning and recommendation engine,  among others. It is suited for two types of audience - those interested in academics and industry professionals looking to upgrade their skills. Hackathons may range anywhere from few hours to few months. Participate here.

OpenML:

This is an open and online ecosystem for machine learning that hosts offline machine learning and data science hackathons. It brings together participants from many scientific domains together to work on industry use cases. It boosts on working with various tools while pushing the scientific community to solve data-driven problems. They also offer tutorials in the field of data science and machine learning. As mentioned, unlike others in the list, this is an offline hackathon platform. Participate here.

In Conclusion

There are various other platforms that host hackathons from various companies which can be both online or offline. Apart from these platforms that are open for participation by everyone, there are many company-specific hackathons conducted by companies such as Intel, IBM and others on timely basis to keep the community connected and abreast with skills in the field. So, the participation is not just limited to the hackathon platforms mentioned in the list, but you can keep exploring for many relevant opportunities to improve skills, get hired or win exciting prizes.

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