Page 29 - Crowdsourcing AI and Machine Learning solutions for SDGs - ITU AI/ML Challenges 2024 Report

Crowdsourcing AI and Machine Learning solutions for SDGs

9 Capacity building

The ITU AI/ML Challenges are not only competitions, but also comprehensive capacity-building
initiatives aimed at enhancing the skills and knowledge of participants in the field of artificial
intelligence and machine learning. These activities are designed to provide participants with
the tools, resources, and mentorship needed to tackle complex real-world problems effectively.
Here are some key capacity-building activities conducted under the ITU AI/ML Challenges:

9.1 Technical Webinars

Experts in AI/ML and related fields conduct webinars to provide in-depth knowledge on various
topics relevant to the challenges. These sessions cover fundamental concepts, advanced
techniques, and specific applications of AI/ML in different domains. Participants gain valuable
insights and stay updated with the latest developments in the field.

9.2 Hands-On Workshops

Workshops are organized to give participants practical experience in developing AI/ML
models. These hands-on sessions guide participants through the process of creating, training,
and deploying machine learning models. By working on real-world datasets and problem
statements, participants can apply theoretical knowledge to practical scenarios.

9.3 Mentoring Sessions

One of the core components of the ITU AI/ML Challenges is the mentoring provided to
participants. Experienced mentors from industry and academia offer guidance on various
aspects of the challenges, including problem-solving approaches, technical issues, and project
management. This personalized support helps participants refine their solutions and enhance
their understanding. As of July 2024, the ITU AI/ML Challenge mentoring activities are on-going
in the following countries: Nigeria, Zimbabwe, Zambia, Tanzania, and Ethiopia.

9.4 Round-Table Discussions

Round-table discussions bring together participants, experts, and stakeholders to discuss
challenges, share experiences, and exchange ideas. These sessions foster a collaborative
environment where participants can learn from each other and gain diverse perspectives on
AI/ML applications and methodologies. These sessions also provide a platform for challenge
participants to clarify issues with challenge hosts as it provides a platform for exchange between
participants and problem statement owners.

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