SDG Challenge

AI for Sustainable Development Goals & SDG-Challenge

Purpose

Learn to apply artificial intelligence (AI) to real-world sustainability problems. This online course blends fundamentals with hands-on practice, preparing you to design, test, and communicate AI solutions aligned with the UN Sustainable Development Goals (SDGs).

Who it’s for

Ambitious students, early-career professionals, data scientists, NGO and public-sector practitioners, and entrepreneurs who want practical AI skills with environmental and societal impact. Basic Python literacy and curiosity are encouraged.

What you’ll learn

• Core AI and machine-learning workflow with TensorFlow and Python data analytics.
• Foundation models (FMs): concepts, opportunities, and risks, with a deep dive into geospatial FM.
• Ethics, bias, fairness, privacy, and accountability in AI systems.
• Team skills for open, reproducible AI projects addressing SDG priorities.

Syllabus & deep-tech focus

You’ll progress from AI fundamentals and SDG context to tools and techniques (TensorFlow, data preparation, modelling), cognitive and ethical foundations, then into application tracks (climate, health, education) with special emphasis on geospatial foundation models (GFM). GFMs are large models trained on diverse spatio-temporal data, offering task-agnostic, sensor-agnostic, and multimodal capabilities for land-cover mapping, change detection, biomass, and climate predictions.

How it’s taught & assessed

Delivery mixes short video lectures, learning slides, and homework. Assessment combines individual quizzes/tests and a project submitted to the SDG Data Challenge and reviewed by experts. Individuals invest 50+ hours to complete the e-learning course.

The SDG Data Challenge

In parallel with the e-learning, participants can join a 4-month challenge with the theme: sustainable forestry. Teams invest 50+ hours to build and evaluate models, with judging criteria including accuracy and computational efficiency; selected algorithms can be turned into an open-source map applet.

Practical information

• Format: 100% online, self-paced with live touchpoints and mentor forums.
• Workload: 50+ hours of course study, and/or 50+ hours of team challenge per team member.
• Cost: The e-learning course and data challenge are free to join.
• Certification: Certificate of achievement for successful completers; digital credential issued by the provider.