Revit API fundamentals, Dynamo for Revit, pyRevit framework, IFC schema and openBIM, model checking, automated documentation, clash detection, and BIM interoperability tools for AEC computational design.
Python calculators for geometry analysis, structural checking, solar calculations, panel optimization, mesh analysis, material estimation, and fabrication cost estimation for AEC computational design.
GIS integration, sensor data, occupancy analytics, space syntax analysis, urban data analytics, climate data processing, and API data sources for evidence-based AEC computational design.
Daylight analysis, solar radiation, energy simulation, CFD wind analysis, thermal comfort, acoustic simulation, and the Ladybug Tools ecosystem for performance-driven AEC computational design.
Evolutionary algorithms, multi-objective optimization, design space exploration, fitness function design, population-based methods, and generative workflows for AEC computational design.
File format encyclopedia, data exchange strategies, API integration patterns, Grasshopper-to-Revit pipelines, Rhino.Inside workflows, Speckle data streams, and schema mapping for AEC computational design.
Computer vision for buildings, image-to-floorplan, generative ML models, performance prediction, structural analysis ML, energy prediction, natural language to design, and point cloud ML for AEC computational design.
Parametric design methodology, data structures, constraint systems, Grasshopper and Dynamo patterns, parameter space exploration, and associative geometry for AEC computational design.
Python for Rhino and Grasshopper (RhinoCommon, rhinoscriptsyntax, ghpythonlib), C# for Grasshopper components, Python for Revit (pyRevit, RevitPythonShell), JavaScript for web 3D (Three.js), and code patterns for AEC computational design.