AI for Revit Users: Python, C#, Add-ins
No coding experience needed. Begin with ChatGPT for Architects to turn sketches into 3D visuals, then build practical automations with a hands-on Python Kickstart. Next, explore pyRevit prototypes and advance to C# add-ins for custom ribbons, tools, and UIs. By the end, you’ll have real, deployable solutions to boost your Revit workflow.
Duration: 30–36 hours
Teaching Methodology: Hands-on, project-based
Course Schedule: Schedule
Fees $900
Course Mode: Blended — Face-to-face or online via Zoom
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OVERVIEW
Turn Revit power users into automation pros. We begin with ChatGPT for Architects to quickly convert sketches into presentation assets (colorized, styled, and 3D/photoreal), then move into a focused Python kickstart in PyCharm. You’ll use pyRevit and ChatGPT to create cleanup tools, data reports, QA/QC checks, and parametric/generative scripts—then convert proven ideas into C# add-ins with ribbons, buttons, and (optionally) a modeless WPF window via ExternalEvent.
Why this blended path (Python → C#)?
| Stage | Tools | Strengths |
|---|---|---|
| Prototype in Python | pyRevit, PyCharm, ChatGPT | Fast iteration, low barrier, excellent for exploring Revit API and validating logic |
| Ship in C# | Visual Studio/Rider, .NET 8, WPF | Performance, typing, maintainability, clean UI, deployment via DLL + .addin |
Time Saved: Estimated Benefits (%)
| Area | Traditional Revit | With AI + Automation (Python/C#) | Improvement (%) |
|---|---|---|---|
| Repetitive Task Automation (views, sheets, exports) | ~3–4 hrs / 100 sheets | ~30 min total | 85–90% |
| Family Parameter Updates (200+ families) | 2–3 days manual editing | < 4 hours (batch script) | 75–85% |
| QA/QC & Standards Compliance | ~1 day per project audit | ~1–2 hours (rule-based scan) | 80–90% |
| Schedule Generation (e.g., furniture/door schedules) | ~0.5 day incl. formatting | < 1 hour end-to-end | 70–80% |
| Rework Reduction (from fewer parameter/schedule mistakes) | Frequent manual fixes & rechecks | Automated checks + guided fixes | 50–70% |
| Overall Project Efficiency | Baseline 100% | 135–150% productivity equivalent | 35–50% overall gain |
Notes: Estimates are based on typical class projects and instructor experience. Actual results vary with model size, standards, and team maturity.
AUDIENCE
Architects, BIM managers, structural/MEP engineers, and tech-savvy professionals who want to automate Revit with AI—quickly and professionally.
PREREQUISITES
No prior coding required — this course is designed to guide you step by step. We recommend completing AI + Python for AutoCAD Users first, especially if you are new to programming or automation, as it provides an easier introduction to Python and AI-assisted scripting in a lighter CAD environment. For learners seeking deeper fundamentals, our Python 1 course is also suggested but not mandatory. A basic understanding of Revit is assumed — if you are new to the software, please complete Revit 1 Fundamentals for All Disciplines first.
CERTIFICATION
ETC is an Autodesk Authorized Training Center. International certificates from Autodesk are issued upon completion.
Frequently Asked Questions
Do I need Python or C# experience?
No. We begin with image/sketch exercises using ChatGPT (visual enhancements, sketch → 3D/render) and a 6-hour Python Kickstart. A C# quick start is included mid-course.
Can I automate my existing Revit models?
Yes. You’ll build cleanup, data extraction, QA/QC, and generative tools and apply them immediately.
COURSE CONTENTS
00 — AI Tools for Architects
- ChatGPT and Nano Banana for Architects
- ChatGPT, Promeai, and Midjourney for Architects
- Runway for Architects
- PDFs, Excel, and ChatGPT for Architects
- Using Meshy AI and Vectorizer AI
- Visualize and Analyze with AI Tools
01 — Quick Introduction to Python
- Install Python & PyCharm
- Python basics: variables, data types, I/O
- Control flow: if/else, loops
- Functions & modules; lists & dictionaries
- pip basics; working with CSV/JSON
- Contextualized to BIM (wall, room, volume examples)
- Mini Project: Areas & volumes calculator
02 — Revit + Python Foundations (pyRevit + ChatGPT)
- Crafting effective prompts to generate pyRevit scripts
- Revit API essentials via AI guidance: Document, Elements, Collectors
- Prompting ChatGPT to select & read model elements
- Best practices: review, test, and refine AI-generated scripts
- Mini Project: Prompt ChatGPT to build a wall-length exporter to CSV
03 — Safe Scripting Patterns (Prompt-Driven)
- Prompting ChatGPT to add Transactions (Start/Commit/Rollback)
- Generating safe
FilteredElementCollectorusage via prompts - Prompt patterns for Parameters I/O (read/write) with guardrails
- Review checklist: selection handling, units, try/except, performance
- Mini Project: Prompt ChatGPT to find walls taller than 4 m and tag/mark them (with a Transaction & summary dialog)
04 — Ribbons & Buttons (pyRevit, Prompt-Driven)
- Prompting ChatGPT to scaffold a pyRevit extension structure
- Prompts to create tabs, panels, and pushbuttons (correct
script.pyplacement) - Adding tooltips, icons, and help links via prompts
- QA prompts: verify button paths, relative icons, and load order
- Mini Project: Use prompts to package the tall-wall script under an “ETC Tools” ribbon with a working button
- pyRevit Ribbon Customization Deep Dive (event-driven buttons, multiple panels, grouping tools)
- Icons & Theming Consistency (best practices for icon sizing, SVG/PNG handling)
- Distribution & Updates (how to share your custom pyRevit ribbon with a team)
05 — Prompt Engineering for Revit Automation
- Prompt patterns; translating between C# and Python
- AI-assisted debugging & refactoring
- Reusable prompt library
- Mini Project: Script-suggester chatbot
06 — Data Pipelines for BIM
- Cleaning data with Pandas (outside Revit)
- Reading CSV/JSON inside pyRevit
- Safe mutations & reporting
- Room data updater from CSV/Excel
07 — Quick Introduction to C# + Visual Studio Setup (for Python Users)
- Installing Visual Studio Community (free) with .NET desktop workload
- Creating a Class Library project for Revit 2026 add-ins
- Adding references to
RevitAPI.dll&RevitServices.dll - Understanding C# vs Python: syntax parallels & strong typing
- Using NuGet packages and managing dependencies
- Compiling and deploying DLLs with an
.addinmanifest in Revit’s AddIns folder - Mini Project: Translate the Sheet Renamer tool from Python → C#, build & load in Revit
08 — Revit C# Add-in Setup (.NET 8, Prompt-Driven)
- Prompt scaffolds to generate ExternalCommand classes (Execute, Result)
- Using prompts to add Transaction wrappers & safe try/catch patterns
- Generating a valid
.addinmanifest via prompts (assembly path, AddInId, VendorId) - Prompting for build/deploy steps (Debug folder, Revit AddIns path, version notes for 2026)
- Post-generation checklist: API refs, namespaces, targets, signing, icons
- Mini Project: Prompt ChatGPT to create a “Hello Revit” ExternalCommand +
.addin; build in Visual Studio and load in Revit
09 — Ribbons & Buttons in C# (Prompt-Driven)
- Create ribbon tabs & panels programmatically
- PushButtonData; tooltips, icons, contextual help
- Mini Project: “ETC Tools” ribbon with two commands
10 — Modeless UI: WPF + ExternalEvent
- Why ExternalEvent; thread-safety
- Simple MVVM window wired to Revit actions
- Mini Project: Prefix Sheets modeless tool
11 — Debugging, Logging & Distribution
- Attach debugger to Revit
- Error handling & rollback patterns
- Packaging for team deployment
- Mini Project: Ship a signed build + README
12 — Capstone Project
- Choose one: Model Cleanup Bot, Data Analyzer, QA/QC Assistant
- Prototype in Python → Ship in C#
- Peer demo & feedback