Day 1 – AI Foundations
1. Day 1 Overview
African Summer School · Day 1
AI Foundations for Weather and Climate
Begin your learning journey by exploring what artificial intelligence and machine learning are, how they can support weather and climate services, and how they should be used responsibly.
Day 1 programme
Morning session
Inauguration and AI/ML fundamentals
Opening ceremony, keynote, participant introductions and an introduction to artificial intelligence, machine learning and deep learning.
Afternoon session
Opportunities, limitations and responsible use
Applications in weather and climate services, data and model limitations, ethical considerations and responsible use in the African context.
Learning outcomes
By the end of Day 1, you should be able to:
- Explain artificial intelligence, machine learning and deep learning.
- Describe the main stages of a machine-learning workflow.
- Identify AI applications in weather forecasting and climate services.
- Recognise limitations involving data, bias, uncertainty and generalisation.
- Discuss responsible AI principles relevant to African institutions.
Your Day 1 learning journey
1. Connect Identify a weather or climate challenge relevant to your institution.
2. Understand Learn the main AI and machine-learning concepts.
3. Explore Examine applications in forecasting and climate services.
4. Reflect Consider limitations, responsibility and institutional needs.
Opening reflection
What weather or climate challenge in your country or institution could potentially benefit from improved data analysis, automation or machine learning?