Customize Your Own Training Curriculum
MWSUG offers a full menu of pre-conference and post-conference training courses. These training classes are learning opportunities which allow you to delve more deeply into a topic. Classes are offered on Sunday prior to the conference as well as Tuesday evening after the conference .
Any of our courses are open to any person who wants to take them. Mix and match courses however you like to suit your needs and interests! Take advantage of this opportunity to build your own custom training curriculum!
Updated 28-July-2025
Course Fees
$175 per half-day class with MWSUG 2025 Conference registration$250 per half-day class without conference registration
Course Schedule
Click on the course title for a short description. Click on the instructor name(s) for biographical information.
Sunday, October 5, 2025
| Course Title (click for description) | Instructor(s) (click for bio) | Time |
| Bee-yond the Basics: Harnessing SAS, SQL, and Python for Data Analytics | Charu Shankar | 8:15 AM - 12:00 PM |
| The Production of Tables, Listings, and Figures (TLF) Using Python, R, and SAS® | Kirk Paul Lafler | 8:15 AM - 12:00 PM |
| Driving Miss Data: Data-Driven Techniques | Richann Watson | 8:15 AM - 12:00 PM |
| Enhanced Graphical Display in SAS® Using the SGPLOT, SGPANEL, and SGSCATTER Procedures | Jim Box & Matt Becker |
8:15 AM - 12:00 PM |
| SQL Master Class | Charu Shankar | 1:00 PM - 4:45 PM |
| Leveraging (and Maximizing) ChatGPT for Python, R, and SAS Users | Kirk Paul Lafler | 1:00 PM - 4:45 PM |
| ODS Workshop: The Output Delivery System from Beginning to End | Jay Iyengar | 1:00 PM - 4:45 PM |
| Mastering the Machine Learning (ML) Toolkit: Training, Tuning, & Interpreting Predictive Models in Python | Ryan Paul Lafler | 1:00 PM - 4:45 PM |
Tuesday, October 7, 2025
| Course Title (click for description) | Instructor(s) (click for bio) | Time |
| Mastering SAS Macros: Building Efficient, Reusable, and Maintainable Code | Vijay Govindarajan | 6:00 PM - 9:45 PM |
| Use the Power to Show with SAS® ODS Graphics | LeRoy Bessler | 6:00 PM - 9:45 PM |
Course Descriptions
Bee-yond the Basics: Harnessing SAS, SQL, and Python for Data AnalyticsCharu Shankar
Sunday, October 5, 2025, 8:15 AM - 12:00 PM
This 4-hour hands-on seminar using SAS viya workbench outlines a structured, five-step approach to data processing—Access, Discovery, Manipulation, Analysis, and Reporting—applied to bumblebee data as a creative parallel to pharmaceutical analytics.This approach showcases the complementary strengths of SAS, SQL, and Python in handling diverse analytical tasks. SAS excels in managing large datasets and creating polished reports with its robust data integration and visualization capabilities. SQL demonstrates its power in querying, aggregating, and organizing relational data efficiently, making it indispensable for structured data exploration and filtering. Python shines in its flexibility and scalability, offering advanced analytics, machine learning capabilities, and dynamic visualizations. By leveraging these tools together in SAS Viya Workbench, analysts can create an efficient, end-to-end pipeline tailored for both exploratory and production workflows, bridging the gap between traditional business intelligence and modern data science techniques.
The Production of Tables, Listings, and Figures (TLF) Using Python, R, and SAS®
Kirk Paul Lafler
Sunday, October 5, 2025, 8:15 AM - 12:00 PM
The streamlined production of Tables, Listings, and Figures (TLFs) in a clinical study represents essential elements of a Statistical Analysis Plan (SAP) by providing answers to regulatory questions along with the necessary support documentation for the clinical data contained in them. Tables are derived from source data and often involve the manipulation of data, listings represent the various reports that are generated in file formats like Rich Text Format (RTF), and figures represent graphical output that provides visual clarity and understanding of the data. This course provides attendees with an introduction to TLF programming production techniques using Python, R, and SAS® software.
Driving Miss Data: Data-Driven Techniques
Richann Watson
Sunday, October 5, 2025, 8:15 AM - 12:00 PM
We have all been there. We write a program based on the data we have. Then, we get new data and we must update the program. Making these updates can be time consuming. Not only must you update the production version of the program, but someone must also update any associated validation or QC programs. Wouldn’t it be nice if there were ways around this? This is where data-driven techniques come in handy. Using detailed examples, you will learn how to write robust code that is ready to handle an unexpected bend in the road! This half-day course will cover advanced techniques such as: discovering and using information about data sets and variables even if it's not known in advance; generating dynamic formats that are based on the data instead of hard-coded into your program; using complex looping structures to control your program flow based on the data; building code on the fly, even from within a DATA step; and much more!
Enhanced Graphical Display in SAS® Using the SGPLOT, SGPANEL, and SGSCATTER Procedures
Jim Box, Matt Becker
Sunday, October 5, 2025, 8:15 AM - 12:00 PM
There are many types of graphics displays that you might need to create daily. In SAS® 9, SAS/ GRAPH introduced a family of new procedures that enable you to create graphs quickly and efficiently. With very little coding effort, you can create effective and attractive graphics that can be as simple as scatter plots and bar charts, or as complex as multi-page classification panels. The new statistical graphics (SG) family of procedures includes SGPLOT, SGPANEL, and SGSCATTER. The SGPLOT procedure creates single-celled graphs that can be constructed with a variety of plot and chart types. The SGPANEL procedure creates paneled graphs in which the paneling is driven by classification variables. The SGSCATTER procedure creates paneled scatter plots and matrices that have support for fitted lines, confidence bands, and computed ellipses. These three procedures are designed with a syntax that is powerful yet concise. In this workshop, we will provide examples that illustrate how you can use these procedures at your organization and work together to complete exercises for you to experience the usefulness of these graphics’ displays!
SQL Master Class
Charu Shankar
Sunday, October 5, 2025, 1:00 PM - 4:45 PM
This workshop is for users wishing to master PROC SQL in a step-by-step approach. PROC SQL is a powerful query language that can sort, subset, join and print results all in one step. Users who are continuously improving their analytical processing will benefit from this hands-on workshop. Participants will learn the following elements to master PROC SQL: understand the syntax order in which to submit queries to PROC SQL; select and calculate columns; Filter Rows; Join tables using join conditions like inner join and reflexive join.
Leveraging (and Maximizing) ChatGPT for Python, R, and SAS Users
Kirk Paul Lafler
Sunday, October 5, 2025, 1:00 PM - 4:45 PM
In an era where AI-driven tools are revolutionizing productivity, ChatGPT has emerged as a powerful virtual assistant for data professionals. This training session introduces Python, R, and SAS users to practical strategies for integrating ChatGPT into their daily programming workflows to boost efficiency, improve code quality, and accelerate learning. Whether you're debugging complex scripts, generating data visualizations, transforming datasets, or exploring statistical methods, ChatGPT can be a powerful tool (or assistant). Attendees will learn how to interact effectively with ChatGPT to get high-quality code suggestions, validate outputs, refactor code, and enhance documentation. The training session includes best practices, prompt engineering techniques, use-case demonstrations, and hands-on exercises tailored to each programming language.
ODS Workshop: The Output Delivery System from Beginning to End
Jay Iyengar
Sunday, October 5, 2025, 1:00 PM - 4:45 PM
This course will give attendees an introduction to the Output Delivery System component of BASE SAS as a reporting tool. It will cover both basic and intermediate/advanced topics in ODS. Specific topics include ODS destinations, ODS Objects, ODS Statements, Formatting with Styles, ODS graphics, Creating Styles using PROC TEMPLATE, and more. Examples will be provided utilizing several SAS reporting procedures, such as PROC PRINT, PROC TABULATE, PROC REPORT and others. Demonstrations in SAS will be run to illustrate ODS concepts and applications for attendees. Attendees should have basic experience with BASE SAS programming, including SAS reporting procedures.
Mastering the Machine Learning (ML) Toolkit: Training, Tuning, & Interpreting Predictive Models in Python
Ryan Paul Lafler
Sunday, October 5, 2025, 1:00 PM - 4:45 PM
This hands-on, half-day workshop is open to all data scientists, statisticians, programmers, machine learning engineers, researchers, and students seeking to train and fine-tune supervised machine learning (ML) models using Python. Attendees will gain practical experience with Python’s open-source libraries to build, fine-tune, and evaluate supervised models for classification and regression tailored to real-world predictive needs. To help attendees master the machine learning toolkit, this workshop helps them develop a range of supervised ML models while learning how to mitigate overfitting and underfitting, evaluate model performance, and interpret results and feature significance. Centered around Python’s scikit-learn (sklearn) ecosystem, this workshop shows attendees an applied, model-driven approach with key concepts including preparing data for ML models, automating data workflows with scikit-learn pipelines, balancing model complexity and interpretability, and understanding bias-variance tradeoffs. Attendees will learn essential data cleaning techniques, perform exploratory data analysis (EDA) to visualize and understand feature relationships, and build end-to-end scikit-learn pipelines. Machine learning algorithms developed in this workshop include LASSO regularized models, decision trees, random forests, and gradient-boosted ensembles for classification and regression. Topics include hyperparameter fine-tuning, feature selection and importance, handling model complexity, and strategies for boosting model performance on unseen data. Attendees will be introduced to SASPy, a Python framework for connecting to a SAS session using the free-to-use SAS OnDemand for Academics platform. Participants will learn how to establish a live SAS connection from Python, extract and transfer SAS datasets, and use them as inputs for machine learning models built with scikit-learn. This integration bridges open-source Python frameworks with validated SAS 9.4 and Viya systems, providing a valuable cross-platform skill set for teams working with both Python and SAS. All attendees will receive the workshop’s PDF slides, an interactive Jupyter Notebook containing the workshop’s documented Python code, the workshop's dataset, and the practical skills to confidently train, optimize, and evaluate predictive models for data-driven AI workflows with integrations to SAS. Attendees will gain practical experience by using libraries from Python’s package repository PyPI includi ng scikit-learn, pandas, numpy, scipy, matplotlib, and seaborn.
Mastering SAS Macros: Building Efficient, Reusable, and Maintainable Code
Vijay Govindarajan
Tuesday, October 7, 2025, 6:00 PM - 9:45 PM
This 4-hour workshop equips SAS programmers with the skills to leverage the SAS macro language for efficient, reusable, and maintainable code. We begin with macro fundamentals, exploring the purpose, creation, and use of macro variables, including their scope and resolution with multiple ampersands. The session progresses to advanced techniques, covering macro programs, conditional logic, iterative loops, and nested macros for complex automation. Attendees will learn to interface macros with DATA steps, create reusable macro code, and extend functionality with custom macro functions and quoting techniques. Practical debugging strategies will address common pitfalls, ensuring robust code. Live examples will reinforce each concept. The workshop concludes with guidelines for building cohesive macro applications, empowering attendees to design scalable, efficient solutions. By mastering these critical and advanced macro programming elements, participants will be equipped to write cleaner, more effective SAS code, avoiding typical errors and harnessing automation for enhanced productivity.
Use the Power to Show with SAS® ODS Graphics
LeRoy Bessler
Tuesday, October 7, 2025, 6:00 PM - 9:45 PM
This is a course for which there is no substitute. It can take you from no experience to proficient at creating charts and plots that enable quick easy understanding of data. Learn best ways to get beyond the defaults, to wise design with SAS ODS Graphics, THE Graphics SuperPower Tool. Not just How To, but What To. ODS Graphics comes with SAS at no added charge. Put its super value to work for your company or client, and yourself. See every kind of plot or chart that the software can do. Learn how to best work with any kind of data, categorical, time series, univariate, or geographic, using my principles of communication-effective graphic design and communication-effective use of color. The course is derived in part from my book, but examples include inventions created since its publication. Students get course notes, a zip file of the code, and a copy of the book Visual Data Insights Using SAS® ODS Graphics: A Guide to Communication-Effective Data Visualization.
Instructor Biographies
Charu Shankar
Charu Shankar, a SAS instructor with a background in computer systems management, engages with logic, visuals, and analogies to spark critical thinking. Prior to joining SAS, Charu served in the United Nations managing educational projects and taught computer and natural languages at Rotman School of Management, University of Toronto. At SAS, Charu curates and delivers unique content on SAS, SQL, Python, Viya, etc. via the SAS YouTube channel, SAS global forum, SAS Ask the Expert Series, SAS Training Post, etc. When not coding, Charu teaches yoga and loves to explore Canadian trails with her husky Miko.
Jim Box
Jim is an accomplished data scientist who has demonstrated an ability to transform insights from analytics into business improvements across a 25+ year career in life sciences and healthcare. He has helped develop SAS’s clinical trial enrollment simulation capability that is used to retarget clinical trials. Jim has a Masters of Science in Analytics and a Masters of Business Administration from NC State University, a Masters of Science in Statistics from Duke University and a Masters of Science in Systems Management from the Florida Institute of Technology.
Jay Iyengar
Jay Iyengar is Director of Data Systems Consultants LLC. He is 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.
Kirk Paul Lafler
Kirk Paul Lafler is a data scientist, developer, programmer, educator, consultant, and author who teaches dozens of in-person and virtual SAS, SQL, Python, R, Analytics, Excel, and cloud-based technology courses, workshops, and seminars to users around the world. Kirk is also a lecturer and adjunct professor at San Diego State University and is a Western Users of SAS Software (WUSS) Executive Committee (EC) Board Member serving as the Open Source Advocate and Coordinator. As the author of several books including PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019) along with hundreds of papers and articles on a variety of SAS topics; Kirk has been selected as an Invited speaker, educator, keynote, and mentor at SAS conferences and meetings worldwide; and is the recipient of 29 “Best” contributed paper, hands-on workshop (HOW), and poster awards.
LeRoy Bessler
Dr. LeRoy Bessler is a data artist, author of the book “Visual Data Insights Using SAS® ODS Graphics: A Guide to Communication-Effective Data Visualization”, the world’s longest serving advocate for and demonstrator of SAS best practices for data graphics and use of color, and a SAS InfoGeographer. He is a consultant, trainer, data analyst, programmer, application developer, and a data visualization aficionado since 1981. He has supported SAS servers, SAS software, SAS data, and SAS users, concurrent with his own work as a SAS practitioner. Besides data visualization, his special interests include human learning, natural intelligence, and software-intelligent application development for reliability, reusability, maintainability, extendability, and flexibility to deliver Strong Smart Systems™.
Matt Becker
Matt is an Advisory Industry Consultant with the SAS Global Hosting and U.S. Professional Services division. Matt’s more than 30 years of life science experience includes over 9 years with SAS concentrating on next generation clinical trials, data management, analysis, advanced analytics, and deployment options in Life Science. As a leader for developing technology solutions to life science initiatives, Becker addresses the challenges that life science companies are having around the analytics lifecycle. The challenges result from new infrastructures that provide more data points than ever before, content management, compliance, collaboration, and analytics. He evaluates existing infrastructures and best practices to provide a road map for the future of life science efficiencies. Recent achievements include solutions in data flow from input to insight to deployment, a visual real-time microbiology antibiogram and an analytics workbench using containers for deployment. Matt’s focus is on finding solutions to change lives via technology, analytics, and science.
Ryan Paul Lafler
Ryan Paul Lafler is the Founder, CEO, Chief Data Scientist, and Lead Consultant at Premier Analytics Consulting, LLC, a data science consulting firm based in San Diego, California. He’s also Adjunct Faculty at San Diego State University for the Big Data Analytics Graduate Program and the Department of Mathematics and Statistics. Ryan’s multilingual experience in Python, R, SAS, JavaScript (React.js & API frameworks), and SQL has contributed to his success as a Big Data Scientist; Consultant; Machine Learning Engineer; Statistician; and Application Developer. He received his Master of Science in Big Data Analytics from San Diego State University in May 2023 following the successful defense and publication of his Thesis. He holds a Bachelor of Science in Statistics and minored in Quantitative Economics from San Diego State University after graduating Magna cum Laude. His passions include Machine Learning, Deep Learning, Artificial Intelligence, statistics, web application and interactive dashboard development, data visualization, and open-source programming languages.
Richann Watson
Richann Jean Watson is an independent statistical programmer based in Ohio who loves to code and is very active in the SAS User Group community. She has been using SAS since 1996 with most of her experience being in the life sciences industry. She specializes in analyzing clinical trial data. When Richann is not busy coding or volunteering in the SAS User Group community, she is spending time with her family and cute but psycho puppy, Loki, or doing some of her favorite crafts such as crocheting or sewing.
Vijay Govindarajan
Vijay Govindarajan has spent over 15 years at SAS Institute, serving in a variety of roles including Developer in SAS R&D, Architect in SAS Services, and Systems Engineer in the Global Technology Practice. He is passionate about SAS programming, data architecture, and analytics. Vijay holds Master’s degrees in Biomedical Engineering (Marquette University) and Data Analytics (Georgia Institute of Technology).