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SAS® Certification Guides

SAS® Certification Prep Guide: Base Programming for SAS® 9, Third Edition

SAS® Certification
Specialist Prep Guide:
Base Programming Using SAS®9.4

SAS® Certification Prep Guide: Advanced Programming for SAS®9, Fourth Edition

SAS® Certified Professional Prep Guide: Advanced Programming Using SAS® 9.4

SAS® Certification Prep Guide: Advanced Programming for SAS®9, Fourth Edition

SAS® Certification Prep Guide:
Statistical Business Analysis Using  SAS®9

Base Programming Credentials: New performance-based exam available.
Choose the credential that’s right for you.

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Author Spotlight

Troy Martin Hughes

Troy Martin Hughes has been a SAS practitioner for more than 20 years, has managed SAS projects in support of federal, state, and local government initiatives. He is the author of three groundbreaking books that model SAS best practices, including SAS® Data Analytic Development: Dimensions of Software Quality (2016), SAS® Data-Driven Development: From Abstract Design to Dynamic Functionality, Second Edition (2022), and PROC FCMP User-Defined Functions: An Introduction to the SAS® Function Compiler (2023).


Kirby Thomas

Kirby Thomas is a Technical Communicator at SAS who enjoys taking complex concepts and breaking them down into easy-to-understand steps. She has over 9 years of experience programming in SAS and is excited to share her lessons learned with new programmers so that they can feel empowered to dive into coding without the hindrance of perfection paralysis. She is author of The Simple Guide to SAS®: From Null to Novice.


Iain Brown

Dr. Iain Brown is Head of Data Science at SAS, specializing in Credit Risk. He has spoken at a number of internationally renowned conferences and conventions and has published papers on the topic of credit risk modeling in relevant journals. He's author of Developing Credit Risk Models Using SAS® Enterprise Miner™ and SAS/STAT®: Theory and Applications and Mastering Marketing Data Science.


Babatunde O. Odusami

Babatunde O. Odusami, Ph.D., CFA, is a professor of finance at Widener University. His research interests are in statistical and machine learning models that can explain how the values and risks of financial assets and portfolios evolve. He's auhtor of Financial Data Science with SAS®.