SAS Viya Workbench
SAS Viya Workbench is a cloud-based, on-demand computing environment that empowers development of advanced analytics, AI and machine learning models using SAS or Python, through Visual Studio Code or Jupyter Notebook interfaces, with minimal IT support.
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Learn More
Visit the SAS Viya Workbench product page
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Get Access
Subscribe to SAS Viya Workbench on AWS
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Documentation
SAS Viya Workbench documentation
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Video Tutorials
Tutorials to guide you through the essential steps to get started
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SAS Viya Workbench Communities Page
Learn about SAS Viya Workbench, our lightweight, standalone development environment built for the creation of high-performance models in your preferred language: SAS or Python.
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SAS Viya Workbench for Learners
Access for free with your university email
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SAS Viya Workbench Examples
SAS and Python code examples for use with SAS Viya Workbench
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SAS Viya Workbench Demos
Comprehensive, industry-specific demonstrations of SAS Viya Workbench capabilities
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SAS Viya Workbench Compatibility
Tools for SAS Viya Workbench administrators to validate environments and tasks
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Python your way: 6 ways to run Python in SAS Viya
Want the flexibility of modern Python development with the power of SAS behind it? Explore how SAS Viya Workbench combines familiar tools, on-demand compute, and Python-native access to advanced SAS algorithms in a single browser-based environment.
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SAS 해커톤 2025 대회에서 한국 ‘블록큐브팀’ 챔피언 선정!
단순한 경쟁을 넘어 사회적 문제를 해결하고 인류의 삶을 개선하기 위한 혁신의 장인 글로벌 SAS 해커톤 대회가 지난 9월 중순부터 10월까지 한 달 간의 흥미로운 개발 여정을 마쳤습니다. 'SAS 해커톤 2025'에는 전 세계 66개국 708개 기업 및 대학, 그리고 SAS 파트너사에서 2,058명의 인재들이 등록하며 뜨거운 관심을 입증했습니다. 이 중 125개의 공식 [...]
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The afterparty: Hyperparameter autotuning revisited
In my first article on hyperparameter autotuning, I used a cake analogy to show how to use hyperparameter autotuning with Optuna and the sasviya.ml package in Python to improve detecting Higgs bosons in a particle accelerator. SAS Viya Workbench now supports hyperparameter autotuning in SAS code with a variety of [...]
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Quickly and easily register Python models in SAS Viya Workbench
Learn how to seamlessly register and deploy Python models (specifically an XGBoost classifier) into SAS Model Manager using SAS Viya Workbench and the pzmm package, enabling efficient ModelOps integration and production readiness.