5 Characteristics That Make Omdena AI Challenges Unique
Why our challenges attract individuals from all around the world to learn and build AI for Good.
As you are reading this you might be interested to join one of our challenges to solve grand societal problems with changemakers in 70+ countries.
With feedback from an ever-growing global community, this article will answer the why & how behind Omdena.
- Learning while making a real-world impact
- Collaboration instead of a competition
- A five-step growth path from Junior to Mentor
- Real-world experience for a diverse and relevant skill-set
- Joining a global community with a common vision
Changing AI education and development
Omdena started to change the status quo, not as an individual or a company, but as a community.
While it seems like the entire world is competing, our mantra is to build AI for Good, By the People, For the People.
We are doing this to enable an environment where AI engineers and enthusiasts from diverse backgrounds can learn from each other, thrive together, and build meaningful careers in AI and Data Science.
Some quick facts
- Challenge duration: two months
- Time commitment: 10 to 20 hours a week
- A real-world problem with a mission-driven organization
- Not a competition! Instead, a collaborative challenge with 40 to 50 data scientists, ML engineers, data engineers, students, and domain experts.
- Communication via Slack and weekly video calls
- Certificates, blog articles, webinar participation upon challenge completion
Apart from the key facts, the following are five community-approved advantages of being an Omdena Collaborator.
#1 Learning while making a real impact
An Omdena challenge starts with a meaningful problem to be solved such as fighting hunger or sexual harassment.
You’ll work on an actual real-world use case with mission-driven startups, NGOs and world-leading organizations.
As Senior Data Engineer Natu Lauchande puts it,
This was the most gratifying learning experience that I have been part of. A team with diverse individuals from different corners of the world working on a meaningful problem-to-be-solved is an incredible boost to the learning process.
ML engineer Mircea who worked in our “climate change and forced displacement Challenge” with the UN Refugee Agency describes his experience as follows,
Among the many things I’ve learned, the most important is that you know that the final product will be used to save people’s lives, what can be more motivating than that?
If you want to know in more detail, how a challenge works, read about three Omdena Collaborators sharing their experiences.
Let us move on.
#2 Collaboration instead of competition
There are no single winners in our challenges.
Instead, collaboration divides the task and multiplies the success for all members.
Once you are accepted into a challenge, you’ll join a team of 40 to 50 other collaborators to tackle the problem at hand.
The problem statement or use case will be broken down into task groups. All of this will be done by the community in a collaborative and self-driven effort.
You are free to lead a task group (based on your experience level) or join a group and contribute.
In the words of Animesh Seemendra:
The best part of this collaboration for me was that many of the collaborators in this team were professional data scientists, some of whom with Ph.D. or more than 10 years of experience in the industry.
If you believe in the power of collaboration, you’ll have a blast!
#3 A five-step-growth path from junior to mentor
While we welcome different experience levels, there is the opportunity to move up in our challenges by taking on more responsibility and work on different roles.
Fred N KIWANUKA, Data Scientist at UNICEF and Research Fellow at MIT,
Meeting so many collaborators following diverging backgrounds and locations working on one challenge as a family has been so rewarding. No matter how experienced or skilled in AI, you will always learn something new from this family of collaborators working for Social Good.
If you are keen to apply, here are some tips on how to make it into one of our challenges.
How To Get Selected For An Omdena Challenge
Everything you need to know to apply and get selected for an Omdena AI challenge.
#4 Real-world experience for a diverse skill-set
Becoming a data scientist or ML engineer is not only about technical skills.
Unfortunately. Most education happens in a controlled environment through courses, papers, and prepared data sets where technical skills play a dominant role.
The real world works differently.
And at Omdena you step into the real world.
With a big portion of self-drive, you’ll need to find creative ways to access and prepare the data, collaborate with others to solve real problems and communicate results to a diverse audience and the public.
An Omdena challenge covers the entire data science project life cycle.
According to Prasanna Muralidharan especially the “empathy” portion of data science is essential in the challenges. As a community we look at important data ethics questions together: what we collect about people, analyze, build models and predictions with. We are fully aware that solutions potentially affect the lives of many people in not just one way.
As a result, you’ll improve data sensitivity and empathy as part of your skill-set.
Project Management and career progress
According to Data Scientist Daniel Ma from Canada,
Aside from going through the motions of developing data science projects (data visualization, wrangling, model development, etc), I felt I was able to exercise some of the best practices in agile project management from my day-to-day. Working with many bright individuals in the industry enhanced my ability to communicate technically.
#5 A global community of changemakers
Lastly, you will become part of a family of purpose-driven individuals from all around the world working together with mission-driven organizations to apply AI in the most demanding fields.
We value openness, an innovation-driven mindset, and the willingness to help each other to thrive.
There is just one more thing to say.
Let’s collaborate! :)