Hackathon! Get Ready with Me 🤓😎
By: Jiwon Jeong
Tags: Hackathons, Artificial Intelligence, Machine Learning, Programming, Data Science

Rather than talking about what I made, however, I’d like to share what I learned in the process. So today, I’m going to talk about the 4 reasons why you should apply for a place in a Hackathon (especially if you’re an aspiring data scientist), how you should prepare and some of my tips. I hope this article can motivate you to go out of your comfort zone and get some profound inspiration just as I did.

1. Why Hackathons

If you haven’t tried a hackathon or a programming competition before, and say you ask me if it’s worth trying, I’ll nod my head without hesitation. Here are the 4 reasons why you should go to a hackathon.

Beyond “modeling”

We, data science learners, tend to work alone or study alone. We tend to invest most of our time in data preprocessing and wangling. And we pour most of our energy into studying machine learning or deep learning algorithms. Our project usually starts with importing data (or sometimes with building data by ourselves) and ends with the evaluation of the predictions.

Almost every real-world project in the world sadly doesn’t work that way. We don’t work alone. We work with other team members. From database to deployment and product management, all the processes should be done through collaboration. Having toolkits beyond the “modeling” territory can be a great plus for aspirants. (Many articles are pointing out this and you can find one here as well) Now the important question, where can we learn and experience this?

“Unlike competitions, nobody gives you two .csv files called train and test and a nicely written evaluation metric. Almost 80% of the efforts go into defining the problem and getting and processing data. Remaining 20% effort goes into pure modeling and deployment.”

A hackathon can be a great chance to collaborate with others and make a real-world project. Although there are some limitations, still you can learn how to communicate with others (who do not have much of the knowledge in machine learning as you do) and understand the overall workflow for releasing an actual product. And if you get a chance of being on the team with someone who knows a lot better than yourself in machine learning, I believe it’ll be such a great time to push your limits as well.

Business thinking is more crucial than you think

The first step of the project will be deciding what to build. And I can tell half of the winning chance is determined here. You should get off on the right foot. Implementation is also a critical point but the business value plays an essential role. If it’s neglected, your work can be nothing but just showing off how technically competent you are.

“Likewise, data scientists are hired to create business value, not just to build models. Ask yourself: How will the outcome of my work influence company decisions? What do I have to do to maximize this effect? With this entrepreneurial spirit, the third wave data scientist does not only produce actionable insights, but also seeks that they bring about real change.”

You’d have seen many people pointing out the importance of business mindset already. Finding a hidden need of users and observing a problem in the market. Suggesting a solution with your technical knowledge. Developing a service that can become profitable. At a hackathon, you are asked to think and discuss deeply with this viewpoint.

I heard of a guy who had won programming competitions more than 15 times. He retired in his ‘prize hunting’ career after he won one of Google’s competitions. Do you know what his secret was? It was just business sense and a little bit of wit. By making a clever and creative product, he made people shout “Brilliant!” which definitely leaves an impression on panels. So if you’re looking for an additional tip for winning, having business values with some wit can be a great bonus.

Great chance to handle extreme stress

The goal of a hackathon is creating a functional product during a short period (commonly 2 or 3 days). You are asked to present a prototype or demo of your product during these days. It’s all about limited time, limited resources and limited energy problems. Sometimes, you could have situations where things go wrong and you’d have to instantly find solutions. Sometimes you have to prioritize your work, which means what to come first and when to stop. You could feel intense pressure to do all your tasks and not to be a burden on the team. And as time passes, becoming completely famished and exhausted is literally inevitable! (More like energy drain or depletion until finally “falling” asleep).

If you’re someone like me, who tend to freeze at an extremely stressful moment, you’d be overwhelmed even by the air at the competition hall. It was my first time in a Hackathon so I experienced my brain being paralyzed several times. I had to get some fresh air and relax to ease off the tension. But this also became a great chance for me to learn how to dealing with stress. Because it’s unavoidable meeting those unexpected problems in the workplace and we have to manage those demanding moments.

The real-time of ”Hello, world”

Meeting new people is also a great pleasure, especially if they are like-minded people. At a hackathon, you can meet various people from different regions and with different specialties but with the same interest. They can be web developers, app developers or designers but they are people who’re willing to invest their weekend in developing something cool.

I met people who came from Russia to Korea just for this event. I also met a Ukrainian lady studying Computer Science in Korea. There were people from Denmark, French, China, and Japan. Meeting new people itself is a great joy. But more than that, I could hear what kind of pain points they have and what they are really passionate about. My horizon could become broadened in programming by chatting with fellow participants. And this is a reason why I think you should try a Hackathon with generous topics rather than heavily focused on the data science fields.

Also, it’d be good to care about what others do as well. Although you’ll be too busy to take extra care of others, this will help you understand the whole process as I mentioned above. We’re here to learn new things, anyway!