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Workshop Curriculum Preview
1. Introduction to AI and Arctic science
• Breaking the ice with AI in Arctic Science
• AI for everyone: an introductory overview
• Guest lecture (Anna)
• The Fun and frontiers of AI: innovation, imagination, interaction
2. Data management and preparation for AI
• AI-ready data in Arctic research: principles and practices
• Guest lecture: unveiling the ARTS dataset for a thawing frontier
• Data annotation: the foundation of deep learning models
• Hands on lab: data annotation
3. AI fundamentals and techniques
• The building blocks of neural networks and deep learning
• Introduction to PyTorch: core functionalities and advantages
• Hands-on-lab: PyTorch
• Exploring advanced neural networks: semantic segmentation
• Introduction to deep learning libraries for image analysis
• Hands-on-lab: MMSegmentation
4. Advanced AI workflows and models
• AI workflows and MLOps: from development to deployment
• Hands-on-lab: AI workflows
• Foundation models: the cornerstones of modern AI
• Hands-on-lab: foundation models
5. Ethics and social implications of AI
• AI ethics
• Socially responsible AI
• Reproducibility
Socially Responsible AI
Overview
Outline
Reference
Socially Responsible AI
Overview
Outline
Reference