Rationale
The overall aim of the UNcode Hackathon is to develop, design, and implement new classification systems that stand on the usage of AI and will lead to improved strategic project programming of UNIDO. The implementation of AI enables the processing of large amounts of data and streamlines data analysis, which produces diverse outcomes with proposed strategic steps.
We, thus, ask:
How to use AI to improve UNIDO's data-driven strategic programming?
Registration form
Challenges
CHALLENGE A
Develop an LLM-based solution identifying all relevant stakeholders (including Donors, Beneficiaries and Partners) and analyzing their involvement across UNIDO’s project portfolio
An analysis of UNIDO stakeholder involvement would optimize the alignment of projects with stakeholders' interests and needs, leading to more targeted and impactful intervention programs.
CHALLENGE B
Develop an LLM-based solution leading to a comprehensive classification system for UNIDO’s project portfolio
A comprehensive and adjustable classification system, enhanced by AI technologies, would enable strategic and agile portfolio planning, management, and analysis.
Bonus challenge
Considering topics touched upon in the above challenges, what are some other areas UNIDO should be focusing on to improve its strategic programming through the help of generative AI? Think out-of-the- box, be creative and innovative!
Expected Outputs
Basic: Prompt engineering
Intermediate (expected level): Working code for automated data extraction and API usage
Advanced (extra points earned): Web interface for configuration and/or visualization
Event dates
Prizes
- Winning Team: Internship at UNIDO and an amazing surprise
- Runner-ups: Small surprises
- All involved students: Certificate of participation
Teams
30 participants (7-8 teams) from WU students + AIESEC Vienna members (non-WU students).
The application will be through a selection process. You can apply either as an individual or a 2-person group to a specific challenge of your choice: CHALLENGE A or CHALLENGE B.
To apply you do not need a profound knowledge of IT. Every student who has an interest and a drive to learn more about AI in the sustainability context is highly encouraged to apply!
Hackathon teams will be created through applicant pairing. Overall, we will have 4 students per team, with a limited number of teams.
Application as a 2-person group or individually
- At least one student possesses experience or knowledge of IT
- At least one student possesses sustainability background
Jury
Jia Zhu - UNIDO Digitalization Lead
Adnan Seric - UNIDO Innovation Lab Manager
Ana Paula Nishio de Sousa - UNIDO Chief of Digital Transformation & AI Strategies
Anita Neumannova - Teaching and Research associate at WU
Soheil Human - Director of the Sustainable Computing Lab and a Research and Teaching Associate at WU
Contact
Anita Neumannova, MSc., MIM
anita.neumannova@wu.ac.at
www.wu.ac.at