Western Users of SAS Software is excited to announce that WUSS Virtual Classes will be returning for the Spring 2026 season. We will be offering several of our most popular live, half-day training classes taught by seasoned industry experts.
These classes are a tremendous value at just $99 per class. All classes are held from 10am to 2pm PT (1pm to 5pm ET). Please click on each class title for a detailed description of the course and information about the instructors.
Last Updated: April 13, 2026
Course Descriptions
R for SAS Programmers: SQL Processing
Sunil K. Gupta
Thursday, March 19, 2026
10:00 AM – 2:00 PM Pacific Time
In this workshop, you will learn about the Tidyverse package since it is a very powerful and a common R package for data management. You will learn about the DPLYR package since it simulates SQL type operations. We will focus on how to query data with select, drop and filter variables and records. In addition, you will learn how to derive new variables as well as how to stream R commands with piping.
While SAS programmers have the data step and Proc SQL, R programmers can leverage piping and DPLYR packages to streamline R functions for multiple SQL tasks. Once intermediate data frames are finalized, data frames can then be sorted, joined and appended together. Finally, summary variables and records can be created by overall or by group variables.
This workshop is designed to increase your confidence to write error-free R syntax as well as review and confirm your results. This workshop is appropriate for beginner R programmers and for experienced R programmers who want structured R SQL learning.
Outline
- View and Display Data Frames
- Query Data with Select, Filter, Recode and Derive
- Pipe Data to Streamline R Functions
- Join, Union, Sort and Rename Variables
- Overall and Group Summary Variables
- Summary Consolidated Records
ODS Workshop: The Output Delivery System from Beginning to End
Jay Iyengar
Thursday, March 26, 2026
10:00 AM – 2:00 PM Pacific Time
This course will give attendees an introduction to the Output Delivery System (ODS) as a component of Base SAS, as well as covering intermediate and advanced ODS topics. Basic topics include ODS Destinations, ODS Statements, and ODS Styles. Intermediate and Advanced Topics include ODS Output Objects, Proc Template, ODS Graphics, and ODS SG Procedures. Examples will be presented using various SAS reporting procedures, such as Proc Report and Proc Tabulate. Demonstrations will be conducted using SAS On-Demand for Academics and SASHELP data sets. Attendees will receive a solid grasp and working knowledge of the output delivery system.
SAS® Macro Magic for Beginners
Kirk Paul Lafler
Thursday, April 9, 2026
10:00 AM – 2:00 PM Pacific Time
Learn to Write SAS Code That Works Smarter, Not Harder
This course introduces macro programming as a productivity tool, not a mystery language by stripping away the confusion and focusing on practical patterns beginners can use immediately. With guided examples and incremental exercises, you’ll learn how to construct macros that automate common tasks such as dataset creation, reporting, and repetitive analyses – perfect for business and analytics environments, and how macros can help you write code once and run it many times – saving effort, reducing errors, and improving consistency across projects.
Key Topics
- Macro basics explained in plain language
- The role of macros in scalable SAS programming
- Creating reusable macro templates
- Conditional macro logic for workflow control
- Using macro parameters effectively
- Macro loops for repetitive tasks
- Debugging and testing macros
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Learning Outcomes
- Confidently read and write basic SAS macros
- Design reusable SAS programs using macros
- Apply looping and parameterization techniques
- Improve code efficiency and consistency
- Understand when macros add value – and when they don’t.
PROC FCMP User-Defined Functions: An Intro to the SAS Function Compiler
Troy Martin Hughes
Wednesday, April 15, 2026
10:00 AM – 2:00 PM Pacific Time
This virtual course follows the general structure and content of the author’s 2026 book: PROC FCMP User-Defined Functions: An Introduction to the SAS® Function Compiler, Second Edition. It provides a gentle introduction to SAS user-defined functions (and subroutines), which enable SAS practitioners to build reusable chunks of code that can be shared among coworkers and teams, and which improve the efficiency and quality of SAS software development. No prior knowledge of PROC FCMP or the SAS macro language is required, and the course will additionally introduce SAS arrays, hash objects, and hash iterator objects, for those unfamiliar with the concepts.
Instruction includes:
- Gentle introduction to PROC FCMP syntax and the construction of user-defined functions and subroutines (using the FUNCTION and SUBROUTINE statements, respectively>)
- Use of the STATIC statement to retain local variables or data structures across function calls
- Passing character and numeric data to functions, and returning these data from functions
- Passing arrays to functions, and declaring and using arrays inside functions
- Use of the OUTARGS option to modify multiple arguments (to pass arguments “by reference” not “by value”)
- Declaring, initializing, and referencing hash objects and hash iterator objects within functions
- Passing hash objects and hash iterator objects as arguments to functions
- Calling functions and subroutines from the DATA step, and using %SYSFUNC and %SYSCALL
- Calling user-defined functions from PROC FORMAT user-defined formats or informats
- Leveraging PROC FCMP to call user-defined Python functions
- Multiple examples demonstrating the superiority of user-defined functions to user-defined macros in solving programming challenges
The course is taught in lecture format, so students are not expected to run the exercises in real-time. However, all SAS code will be provided to students prior to the start of the course, so students have the option to run all examples in real-time during the course, or to peruse the code at their leisure after conclusion of the course.
Next Generation AI for Biometrics: From Gen AI to Agentic Workflows and Vibe-Coding
Kevin Lee
Friday, April 17, 2026
10:00 AM – 2:00 PM Pacific Time
Artificial Intelligence is rapidly evolving beyond simple chatbots into a new era of AI Agents, Agentic Workflows, and Vibe-Coding – where machines can reason, act, and collaborate like digital teammates.
In this hands-on training, we’ll explore how Generative AI (Gen AI) tools such as ChatGPT, Copilot, Gemini, and Claude are transforming the Biometrics field – from automating data analysis and code generation to driving intelligent workflows and decision support.
You’ll learn how to harness these technologies to:
- Build powerful prompt using Prompt Engineering (e.g. Zero Shot, Few Shot, Chain of Thought)
- Enhance data exploration, visualization, and interpretation
- Develop SAS, R, and Python programming using Gen AI
- Translate legacy code across languages effortlessly
- Build data-aware AI assistants that can query and explain datasets
- Develop applications powered by Gen AI APIs, LangChain, and RAG
- Design AI Agents that think and act autonomously within your workflow
- Implement Agentic Workflows that connect tools, data, and reasoning chains
- Explore Vibe-Coding, the next evolution of collaborative human-AI coding
We’ll also discuss risk management, data privacy, and ethical AI practices, ensuring your implementation is both powerful and compliant. By the end of this training, you’ll not only understand how Gen AI works — you’ll be ready to build, deploy, and scale AI-driven solutions in real-world Biometrics environments.
Utilizing National Healthcare Survey Data in Research and Analysis Using SAS
Jay Iyengar
Wednesday, April 22, 2026
10:00 AM – 2:00 PM Pacific Time
This course is intended for programmer\analysts and researchers in the public health domain who need to learn how to access and analyze healthcare survey data. Attendees will learn about the different types of national healthcare surveys, such as the NHANES (National Health and Nutrition Examination Survey), the NHIS (National Health Interview Survey), MCBS (Medicare Current Beneficiaries Survey) and the MEPS (Medical Expenditure Panel Survey). They’ll receive a background and explanation of the surveys and survey data sets. Attendees will also learn how to access, extract and analyze healthcare survey data sets. The course will include demonstrations using SAS to perform a series of tasks with the survey data.
From RECIST to Kaplan-Meier: Building Oncology Trials the Right Way
Kevin Lee
Friday, May 1, 2026
10:00 AM – 2:00 PM Pacific Time
Compared to other therapeutic studies, oncology clinical trial studies are generally complex and difficult for programmers, statisticians and data managers. There is more to understand and to know such as different clinical study types, specific data collection points and analysis. In this training, programmers and statisticians will learn oncology specific knowledge in clinical studies and will understand a holistic view of oncology studies.
- Clinical Study Type
- Response Criteria
- Data Collection
- Analysis
Programmers, statisticians and data managers will also find out what makes oncology studies unique and learn how to lead oncology study projects effectively.
The training will cover four different sub types and their response criteria guidelines.
- The first sub type, Solid Tumor study, usually follows RECIST (Response Evaluation Criteria in Solid Tumor).
- The second sub type, Immunotherapy study, usually follows irRC (immune-related Response Criteria).
- The third sub type, Lymphoma study, usually follows Cheson.
- Lastly, Leukemia studies follow specific guidelines (e.g., IWCLL for Chronic Lymphocytic Leukemia).
The training will show how to use response criteria guidelines for data collections and response evaluation.
Programmers, statisticians and data maangers will learn how to create SDTM tumor specific datasets (RS, TU, TR), what SDTM domains are used for certain data collection, and what Controlled Terminology (e.g., CR, PR, SD, PD, NE) will be applied. They will also learn how to create Time-to-Event ADaM datasets from SDTM domains and how to use ADaM datasets to derive efficacy analysis (e.g., OS, PFS, TTP, ORR, DFS) and Kaplan Meier Curves using SAS Procedures such as PROC LIFETEST and PHREG.
Finally, programmers and statistician will understand how to build end-to-end standards driven oncology studies from protocol, study sub-types, response criteria, data collection, SDTM, ADaM to analysis.
Advanced SAS® DATA Step Programming Techniques
Josh Horstman
Wednesday, May 6, 2026
10:00 AM – 2:00 PM Pacific Time
To solve complex coding problems with the SAS® DATA step, one must go beyond a basic understanding of the individual statements. You need to understand how the various statements interact with each other and how their options can be leveraged to build DATA step code that provides innovative solutions to the toughest of problems. Based on Art Carpenter’s book, Carpenter’s Guide to Innovative SAS® Techniques, this class is a must for the DATA step programmer who wants to take his or her programs to the ‘next’ level.
Topics include:
- Working across multiple observations using look-ahead and look-back techniques
- Employing the DOW loop
- Taking advantage of double SET statements
- Working with hash objects
- Performing table lookups
- Using arrays to transpose data from columns to rows and back again
- Evaluating complex expressions
- Applying data set options
- Adopting new DATA step functions (and old functions with new options)
- And more!
This course is designed to be taken by a student who has a basic understanding of the DATA step and its primary statements. The material will focus on advanced topics that will give the student a deeper understanding of the operation of the DATA step. Through examples, students will be exposed to innovative techniques for solving difficult programming problems.
Fundamentals of Artificial Intelligence: Ready to Move Beyond AI Hype? Build Real Skills That Matter!
Lida Gharibvand
Friday, May 8, 2026
10:00 AM – 2:00 PM Pacific Time
Artificial Intelligence isn’t a future trend — it’s today’s strategic differentiator. From scalable machine learning pipelines to autonomous generative agents and intelligent copilots, modern AI technologies are redefining how professionals extract insight, streamline operations, and engineer high-impact solutions at scale.
Join this high-impact training and master the modern AI stack
You’ll dive into:
- Distinguish major AI paradigms and deep learning architectures
- Apply prompt engineering and structured LLM comparison methods
- Use AI tools for research, coding, and data exploration
- Evaluate AI outputs critically, including hallucination risks
- Integrate AI-assisted workflows into professional practice
- Work with GitHub Copilot, Cursor, Kaggle, and leading LLM platforms
This is not theoretical. You’ll use real tools, test prompts, and evaluate model outputs in production-style workflows. Leave ready to build faster and use AI as a true analytical co-pilot — not just a chatbot.
Learn not just how AI works — but when to trust it, challenge it, and deploy it for measurable impact
Introduction to R from a SAS Programmer’s Perspective
David Bosak
Friday, May 15, 2026
10:00 AM – 2:00 PM Pacific Time
This class will provide a hands-on introduction to the R language, but from the perspective of a SAS® Programmer. It is geared toward someone who has knowledge of SAS, but little to no knowledge of R. SAS and R differ in some fundamental ways. Reviewing these differences will speed up your understanding of R, and greatly reduce potential confusion. The course will start with a brief history of R, and then go into some elementary R topics like vectors, operators, and data frames. We will then perform some common tasks: loading data, performing basic data manipulation, and writing a report. Throughout the session, you will both review existing code and write some code yourself. If you are a SAS programmer who is looking to get a jump-start in R, then this course will be of interest to you.
Asking Better Questions: The Art and Science of Survey Design
Tasha Chapman
Tuesday, May 19, 2026
10:00 AM – 2:00 PM Pacific Time
(Rescheduled from March 5)
Surveys are one of the most powerful tools for understanding customers, clients, and stakeholders, but only when they’re designed well. In this class we’ll take a break from coding and lean into the softer sciences, focusing on the human side of data: how people think, interpret, and respond to questions.
Drawing on human-centered design, behavioral insights, and proven survey methodology, you’ll learn how to write clear, engaging questionnaires that produce reliable, meaningful insights. The concepts learned will apply in any context where your data comes directly from people, whether you’re running a customer survey, gathering user stories, or facilitating lessons learned at the end of a project.
You’ll explore how small wording and design choices can dramatically affect response rates, data quality, and trust in your results. By the end of the class, you’ll be able to design surveys and other data-collection tools that produce insight-driven, decision-ready data.
This class is designed for anyone who uses data to gather feedback, measure perceptions, or inform decisions, including analysts and researchers, business and program staff, and product, policy, or customer experience teams.
SQL – The Grammar behind AI: AI depends on data – SQL makes that data usable.
Charu Shankar
Wednesday, May 27, 2026
10:00 AM – 2:00 PM Pacific Time (cancelled)
This seminar shows how SQL supports every stage of the AI workflow, from data preparation and feature engineering to validation and deployment. Strong SQL leads to better models, clearer logic, and more reliable results.
Participants will work through examples to structure training data, build meaningful features, and identify data issues that affect model performance. The session also highlights how modern analytics platforms integrate machine learning within SQL environments.
Designed for analysts and programmers, this seminar focuses on practical skills that help teams move AI from concept to production.
Meet the Instructors
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David Bosak has been a technology consultant for 28 years. He has extensive experience creating solutions in SAS, R, .NET, database, and Web Technology. Currently obsessed with R, he has become an active package developer, and is the author of 12 R packages. |
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Tasha Chapman has been using SAS since 2003 and an active member of the SAS User Community since 2006. Throughout her career she has championed continuing education and professional development, presented trainings and workshops at professional conferences across the country, sat as an executive committee member on nationally recognized associations, and founded two organizations dedicated to educating colleagues about research, data, and statistics. She was the chair of the Western Users of SAS Software Conference and Educational Forum in 2017 and 2022.
Tasha received a Master’s Degree in Psychology, with an emphasis on personality assessment and psychometrics from the University of California, Riverside. Since 2005 she has worked as a lead research analyst providing data and policy analysis in state government, insurance, and occupational safety and health. She lives in Salem, Oregon with her two adorable kids. |
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Dr. Lida Gharibvand is a Professor and Director of Statistics and Research Education at Loma Linda University, where she teaches statistics and health research courses across various departments within the School of Allied Health Professions. Her expertise encompasses quantitative research, study design, and pedagogical best practices aimed at accelerating student development and performance. Dr. Gharibvand’s research interests focus on air pollution, cancer, public health, geriatrics, medical science, and oncology. She holds a Ph.D. in Epidemiology from Loma Linda University, an M.S. in Applied Statistics from the University of California, Riverside, and an M.S. in Mathematics from the University of Nevada, Reno. |
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Sunil K. Gupta is a strategic advisor to Verisian, an AI technology based software company for better traceability of clinical trial submissions. Sunil, MS, is an international speaker, best-selling author of five SAS books, and a global SAS/R Developer and CDISC SME and corporate trainer. Sunil is an advocate of CDISC automation and standardization with over thirty years of experience in the pharmaceutical industry. Most recently, Sunil is teaching Practical R for SAS Programmers and a CDISC online class at the University of California at San Diego at UCSD Extension. In 2019, Sunil published his fifth book, Clinical Data Quality Checks for CDISC Compliance Using SAS and in 2011, Sunil launched his unique SAS mentoring blog, SASSavvy.com, for smarter SAS searches and R-Guru.com for R Self-Study Class and Mentoring programming. Sunil has MS in Bioengineering from Clemson University and a BS in Applied Mathematics from the College of Charleston. |
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Josh Horstman is an independent statistical programmer based in Indianapolis with 28 years’ experience using SAS in the life sciences industry. He specializes in analyzing clinical trial data, and his clients have included major pharmaceutical corporations, biotech companies, and research organizations.
A SAS Certified Advanced Programmer, Josh loves coding and is a frequent presenter and trainer at industry conferences and SAS user group events. Josh holds a bachelor’s degree in mathematics and computer science, and a master’s degree in statistics from Colorado State University. |
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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, and is a SAS Certified Advanced Programmer, SAS Certified Base Programmer, SAS Certified Clinical Trials Programmer, and SAS Certified Professional V8. He has given more than 180 presentations, trainings, and hands-on workshops at SAS conferences, including at SAS Explore, SAS Global Forum, SAS Analytics Experience, WUSS, SCSUG, SESUG, MWSUG, PharmaSUG, PHUSE, BASAS, BASUG, and MSUG. He has authored three groundbreaking books that model software design and development best practices:
Troy has an MBA in information systems management as well as other credentials, including: PMP, PMI-RMP, PMI-PBA, PMI-ACP, SSCP, CISSP, CSSLP, Network+, Security+, CySA+, CASP+, Cloud+, CISA, CGEIT, CISM, CRISC, ITIL Foundation, CSM, CSD, A-CSD, CSPO, CSP, CSP-SM, CSP-PO, and SAFe Government Practitioner (SGF). He is a US Navy veteran with two tours of duty in Afghanistan. |
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Jay Iyengar is Director of Data Systems Consultants LLC. He’s a SAS consultant, trainer, and SAS Certified Advanced Programmer. He’s been an invited speaker at several SAS user group conferences (WIILSU, WCSUG, SESUG) and has presented papers and training seminars at SAS Global Forum, Pharmaceutical SAS Users Group (PharmaSUG), and other regional and local SAS User Group conferences (MWSUG, NESUG, WUSS, MISUG). He was co-leader and organizer of the Chicago SAS Users Group (WCSUG) from 2015-19. He received his bachelor’s degree from Syracuse University in Public Policy and Economics, and his master’s degree from the American University. |
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Kirk Paul Lafler is a globally recognized data scientist, consultant, educator, programmer, author, and speaker with more than 40 years of experience delivering practical, real-world analytics training. His expertise spans SAS, SQL, Python, R, databases, big data, AI, machine learning, and cloud technologies. Known for transforming complexity into clarity, Kirk helps learners build confidence and proficiency through hands-on, applied instruction.
As the creator and developer of numerous courses, workshops, and publications, Kirk empowers organizations, professionals, and students to think critically, solve complex problems, and make data-informed decisions. Whether training corporate teams or authoring technical content, he connects people with knowledge that drives meaningful impact. Kirk also serves as an Adjunct Professor for the Department of Mathematics and Statistics at San Diego State University (SDSU) and is the co-developer and educator of the SAS Programming certificate program at the University of California San Diego Extension. Kirk is also the author of several books, including PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press, 2019), and has written numerous papers and articles. He is a frequent invited speaker, educator, and keynote presenter at conferences, symposiums, and professional summits worldwide, and a recipient of 29 “Best” awards for contributed papers, hands-on workshops (HOWs), and posters. |
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Kevin Lee is a passionate Data Scientist and esteemed Biometrics Leader, boasting two decades of experience in cutting-edge technology in Biometrics, CDISC, Oncology, Big Data, Cloud, Open-Source Programming, Data Sciences and Gen AI within the pharmaceutical industry. His enduring enthusiasm for leadership and innovative technologies has helped him to drive continuous innovation in the Biometric department.
Recently, Kevin had two aspirations to love talking about – Gen AI and Oncology. Kevin always loves oncology studies and is an active supporter on standard-driven processes using CDISC and response criteria in oncology studies. And also, Kevin has found renewed excitement in the immense potential of Gen AI, particularly in its applications within Biometric department. He is eager to contribute his wealth of knowledge and expertise in CDISC, Oncology, Gen AI, and AI Agentic to the dynamic realm of the Biometric Department by pushing the boundaries of technological advancement and leadership. As a lifelong learner, Kevin takes pleasure in sharing his extensive knowledge, having delivered around 200 papers. Beyond corporate boundaries, he extends his expertise by imparting insights both in academic and corporate settings. |
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With a background in computer systems management, SAS Instructor Charu Shankar engages with logic, visuals, and analogies to spark critical thinking since 2007. Charu curates and delivers unique content on SAS, SQL, Viya, etc. to support users in the adoption of SAS software. When not coding, Charu teaches yoga and loves to explore Canadian trails with her husky Miko. |