Youth in AI – Omdena’s Youth Participating in Real-World AI Projects

Omdena’s community has a lot of promising talents. An inspiring story of Gianni Cettolo, who represents youth in AI. An Argentinian freshman who has just finished one of Omdena’s real-world AI projects shares his motivations for going into the AI field.

By: Gianni Cettolo

Can you briefly introduce yourself, Gianni?

My name is Gianni Cettolo and I am 17 years old. I am studying in a Technical School in Argentina (ITPA). I am truly passionate about Artificial Intelligence and Data Science and how their practical applications are changing and will keep changing the world. I have done many courses and specializations on this topic. I have acquired experience through individual projects, like a face recognition attendance system for my school, and real projects such as Omdena challenges, and now I am participating in a research project in the area of Self-Supervised learning. I am a very curious person so I use every chance I have to learn new things and try to apply that knowledge in the real world. For example, I have been trading the markets for a year and a half after educating myself on the various aspects of that field. I am looking to develop my entrepreneurial mindset and participate in more challenging and impactful projects.

Why do you think it’s important for more young people to explore Data Science?

From my perspective, being able to apply the same concepts to so many different areas is amazing, and many of the problems being solved with Data Science have a huge positive impact. Also, as it is a rapidly growing field, you have to be in touch with the state of the art technologies. It is a place where communication skills and team effort are crucial. The tools and concepts to grasp are not as scary as they seem, that is why I strongly encourage young people to get involved.

What has been your experience with Omdena, and how has that impacted you?

My experience with Omdena was wonderful. I had the opportunity of participating in Omdena’s Challenge “Building a Recommendation Engine for Energy Solutions to Increase Sustainability and Energy Efficiency in Buildings” as a Jr. Machine Learning Engineer. After an amazing team effort, we deployed a web-based application that uses an AI classification model to determine suitability for lighting projects based on ROI estimates. I got to work with a big group of very professional and smart people from 15 different countries that were willing to help, collaborate and teach every time it was needed. The environment was always respectful and you could notice that everyone cared about the project. I learned a lot and gained real experience handling and pre-processing a huge amount of data, developing the machine learning algorithms for the product, getting familiar with the deployment part, and finally communicating inside the project and the results to the business owners. I have done courses and specializations but those are really different from what happens in reality, being in an Omdena challenge helps you see the full picture and now I feel more comfortable tackling new challenges.

When did you first realize your passion for Data Science?

I first realized my passion for AI and Data Science when I noticed the huge amount of positive applications it has. Seeing how much it has changed our lives in the past decade and thinking of the possibilities in the future motivated me to get into the field. I even tried to make my small contribution by making this short video, trying to explain Neural Networks and the Math behind them in a simple way. I also recommend watching YouTube’s series “The Age of A.I.” to see the potential this has.

Did you face any setbacks in your journey thus far? How did that affect you?

Because I discovered my passion for AI and Data Science mainly in quarantine I did not have anyone to share my experiences and improvements with, everything was completely on my own. What I did to overcome this was to organize myself as much as possible and instead of trying to memorize things, I looked for a course in which I was constantly asked to work on projects and share my experience and issues with online communities. I also got used to learning online, which is completely different from a common class. Now I understand how important it is to be in a collaborative environment and enjoy the process with people in similar situations.

How have you approached your previous projects?

At the beginning of a project in Data Science, the best thing to do is focusing on understanding the domain knowledge as much as possible. It is super useful when preprocessing the data, understanding the relationships between certain factors and ultimately being in the shoes of the business owner who needs a real solution (not just a high accuracy on the testing set). Then you can focus on creating powerful models that work successfully. One key takeaway from this part is that changing between various models can improve accuracy by a few percent, but having a Data-Centric approach and working on the data available can make huge improvements. I also learned that there are no dumb questions and that communicating confidently and openly with your teammates is vital.

Where do you see yourself in the future?

I definitely want to pursue a career in AI, Data Science, or Finance. I see myself taking ideas to reality, being an entrepreneur in one or more of those fields, trying to solve impactful and interesting problems.