ARC 401E - Apply.Data Sci.&Mach. Learning

Course Objectives

1. Introducing the general approach of AI and ML
2. Giving knowledge about the architectural data
3. Examining different data types and procedures, data annotation
4. Feature extraction, correlation between input and output

Course Description

Artificial intelligence (AI) is the application of simulating human intelligence to
machines, which makes them think and act like humans beings and therefore
imitate people’s actions. Machine learning (ML) is a branch of AI, which uses
algorithms to find patterns in large datasets and create predictions
accordingly. In one way, AI and ML technologies reconstruct professional
practices. This course will use significant examples from architecture to cover
major machine learning tasks including regression, classification and
clustering. Built environment data will be used for better decisions and
predictions. Data driven design, data analysis and interpretation will be
elaborated. Lectures will both cover the fundamental computational
explanations and architecture based cases regarding to specific machine
learning algorithms.