Select computational methods appropriate to archaeological evidence
Human & Social Systems · Anthropology & Archaeology
ARCH-365AI-Assisted Archaeology
Applies machine learning, computer vision, language models, and spatial computation to archaeological data with explicit validation and interpretive controls.
Course outcomes
What students develop
Prepare and document archaeological datasets
Validate algorithmic classifications against expert and contextual evidence
Communicate uncertainty and interpretive limits
Course content
Topics and questions
- Computer vision and object classification
- Remote sensing and feature detection
- Text mining and archival archaeology
- Predictive modeling and bias
- Validation and explainability
Methods & resources
Tools and environments
- GIS and raster analysis
- Python or notebook environment
- Image annotation tools
- Version control
Evaluation
Demonstration of learning
- Dataset documentation
- Model validation report
- Applied archaeological analysis
Program relationships
Where this course fits
Core
Digital Archaeology & Heritage Science
Connects archaeological method to GIS, remote sensing, 3D digitization, materials analysis, research computing, and digital stewardship.
Core
AI in Anthropology
AI-assisted qualitative, archaeological, spatial, and comparative research with verification, context, ethics, and transparent workflow.
Core
AI-Assisted Archaeology
Computer vision, geospatial computation, archival text analysis, data preparation, validation, and archaeological interpretation.
Course inquiry
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