This session aims to introduce AI to a non-specialist audience, ensuring that participants from any background can understand fundamental concepts.
Focus: explain key terminology and the basic principles of machine learning and deep learning.
Goal: By the end of this session, participants will have a solid foundational knowledge of key AI concepts, enabling them to better appreciate and engage with more advanced topics in the following sessions
Concepts to cover: ML, DL, NN, CNN, datasets and annotations, training and inference, accuracy and validation, supervised learning, etc.
About
This session aims to introduce AI to a non-specialist audience, ensuring that participants from any background can understand fundamental concepts.
Focus: explain key terminology and the basic principles of machine learning and deep learning.
Goal: By the end of this session, participants will have a solid foundational knowledge of key AI concepts, enabling them to better appreciate and engage with more advanced topics in the following sessions
Concepts to cover: ML, DL, NN, CNN, datasets and annotations, training and inference, accuracy and validation, supervised learning, etc.
Resources
This introductory session about ML developed by Yili Yang from Woodwell Climate Research Center is a good model for what we'd be aiming for: