Throughout the hackathon, you will have the opportunity to engage in challenges that will put your creativity and problem-solving skills to the test. Expect to participate in interactive workshops led by industry experts, where you will learn how to build a highly functional minimum viable product (MVP). Be prepared to dedicate a significant amount of time to the development and refinement of your MVP as you strive to create a practical solution that addresses the challenge at hand. Whether you are an experienced hackathon participant or joining for the first time, the GenAI Hackathon 2023 offers the perfect platform to push yourself, acquire new skills, and connect with like-minded individuals who share your enthusiasm for generative AI.
You should start by familiarizing yourself with the use case themes and choose the one that aligns with your interests and skills. You should also take some time to review the guidelines of the hackathon, which will be provided to you ahead of time. Additionally, you may want to consider forming a team with colleagues who have complementary skills and expertise. Finally, be sure to come to the event with an open mind and a willingness to collaborate and innovate. We can't wait to see what you create!
Completion of the Generative AI training at Google Cloud Summit between June 19-22, 2023 is required to participate in this hackathon.
A hackathon is best described as an "invention marathon". Developers, designers, and business people come together to form diverse teams and build collaborative projects to solve a problem or challenge. Over the course of 2 weeks, teams will engage in learning workshops, ideate within their team, design and develop a solution, receive support from mentors, and pitch to judges to compete for prizes
As a hacker, you will collaborate with your team to establish a strategy, and assign roles, and responsibilities in order to create a solution for your minimum viable product (MVP). Throughout the hackathon, you will participate in a series of virtual workshops, conduct product research to deepen your understanding of the challenge and engage in hands-on design and development to present your solution to a panel of judges.
This is a 2 week hackathon with approximately a 20-hour total commitment. Each week there will be 5-6 hours of live workshops and another 5-6 hours to complete deliverables. If you are unavailable for a portion of the event, please ensure your team is aware and can accommodate your absence accordingly.
All skillsets are welcome. We highly encourage diverse and multi-disciplinary teams for the hackathon. We have seen the greatest success in teams with the highest level of diversity. Typical skillsets at hackathons include Developers, Designers, Marketers, Sales, Business Strategists, Idea Generators, Data Scientists, etc.
We also welcome participants from all departments (Technology, HR, Finance, Legal, etc.) to participate and provide your unique perspective on opportunities and problems to be solved in innovating with McDonald's.
No problem! You will have plenty of opportunities to get inspiration by reviewing the Challenges of the event and attending office hour sessions where you can get personalized responses to your questions. You can use this as an opportunity to learn how to code, use no-code tools, design a prototype, or work on refining the business aspects or presentation pitch for your team! In summary, there are many ways to be involved, even if you don’t know how to code.
The hope and expectation is that at least one of your teammates will be able to attend Kickoff and be there for your pitch during Judging. We know that participants are spread out globally, and in some cases, this may be tough.
For Judging, you may upload a video in lieu of being available live for Judging, but this may disadvantage your team if no one on your team is available to answer questions from judges.
No Capgemini data may be used - this includes, but is not limited to, any sensitive data, internal, or client data. Participants can, however, look for public data sources (example: Kaggle).
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