MWSUG 2024 Training Classes

Customize Your Own Training Curriculum

MWSUG offers a full menu of pre-conference training courses. These training classes are learning opportunities which allow you to delve more deeply into a topic. Classes are offered on the Friday, Saturday, and Sunday prior to 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! Discounts are available when you take multiple classes (see below for fees). Take advantage of this opportunity to build your own custom training curriculum!

Course Schedule

Click on the course title for a short description. Click on the instructor name(s) for biographical information.

Friday, November 15, 2024

Course Title (click for description)	Instructor(s) (click for bio)	Time
Python Programming with Scikit-Learn: Developing, Fine-Tuning, and Evaluating Supervised Machine Learning Algorithms for Classification and Regression Tasks	Ryan Paul Lafler	8:00 AM - 5:00 PM
Advanced Programming Techniques Using SAS®	Kirk Paul Lafler	8:00 AM - 12:00 PM
Advanced DATA Step Programming Techniques	Josh Horstman	1:00 PM - 5:00 PM
Automate Manual Excel and PDF Report Creation with Dynamic SAS® Code Your newest BFF (Best Friend Forever) in SAS	Kent Phelps	1:00 PM - 5:00 PM
PROC SQL Programming Masterclass Using SAS®	Kirk Paul Lafler	1:00 PM - 5:00 PM

Saturday, November 16, 2024

Course Title (click for description)	Instructor(s) (click for bio)	Time
From %MACRO to %MEND: Getting Started with SAS Macro Language Basics	Josh Horstman	8:00 AM - 5:00 PM
Joinless Join: The Impossible Dream Come True Using SAS® Enterprise Guide®, PROC SQL, and DATA Step	Kent Phelps	8:00 AM - 12:00 PM
Get Your Report to Excel, PDF, or the Web	LeRoy Bessler	8:00 AM - 12:00 PM
Programming by Example: Applied Statistical Modeling for Hypothesis Testing Using R	Ryan Paul Lafler	8:00 AM - 12:00 PM
Create Charts and Plots That Are Quickly Easily Understood	LeRoy Bessler	1:00 PM - 5:00 PM

Sunday, November 17, 2024

Course Title (click for description)	Instructor(s) (click for bio)	Time
Regression Expression! 24 Regression Methods in SAS	David Corliss	8:00 AM - 5:00 PM
ODS Graphics I: Creating Quick and Easy Graphs with the Statistical Graphics (SG) Procedures	Josh Horstman	8:00 AM - 12:00 PM
Favorite FunKey Functions: Functions for Your Programming Toolbox	Richann Watson	8:00 AM - 12:00 PM
CS 301: Issues in Managing Reuse of SAS programs, Datasets and Catalogs	Ron Fehd	8:00 AM - 12:00 PM
The SASSY System	David Bosak	1:00 PM - 5:00 PM
Working with Medicare and Medicaid administrative data sets using BASE SAS programming	Jay Iyengar	1:00 PM - 5:00 PM
Driving Miss Data: Data-Driven Techniques	Richann Watson	1:00 PM - 5:00 PM

Course Fees and Registration

Course Descriptions

Python Programming with Scikit-Learn: Developing, Fine-Tuning, and Evaluating Supervised Machine Learning Algorithms for Classification and Regression Tasks
Ryan Paul Lafler
Friday, November 15, 2024, 8:00 AM - 5:00 PM

This full-day Python programming workshop is open to all data scientists, business analysts, statisticians, programmers, Machine Learning engineers, researchers, students, and educators interested in developing, optimizing, and fine-tuning supervised Machine Learning algorithms for regression and classification tasks using Python. Whether you’re coming from SAS, R, or another language, this Python workshop will give attendees the confidence to leverage Python’s open-source libraries for data processing, data visualization, and applied supervised Machine Learning. Starting simple and then incrementally building towards more advanced Machine Learning algorithms, attendees are taught practical strategies to mitigate overfitting and underfitting, reduce sources for training bias, evaluate their algorithm’s performance, and interpret their algorithm’s results. All algorithms are developed in Python using the popular Scikit-Learn library, giving attendees an application-oriented approach to using each algorithm, including discussions about the advantages and disadvantages of using one algorithm over another. The supervised Machine Learning algorithms developed in this course includes penalized regression models (Elastic Nets); Decision Trees; Random Forests; and Gradient Boosting ensembles for regression and classification tasks. Topics include hyperparameter tuning; generalizing algorithms for better predictions on unseen data; and leveraging Python libraries like Scikit-Learn, Pandas, NumPy, SciPy, Matplotlib, and Seaborn to efficiently process, clean, and visualize data for training supervised Machine Learning algorithms. By enrolling in this workshop, attendees receive the PDF-slides, interactive Jupyter Notebooks containing the documented Python code, and the confidence to train, fine-tune, and evaluate supervised Machine Learning algorithms tailored to their organization’s needs.

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Advanced Programming Techniques Using SAS®
Kirk Paul Lafler
Friday, November 15, 2024, 8:00 AM - 12:00 PM

SAS® software offers numerous programming constructs to perform amazing programming techniques. This course provides users with valuable skills to help expand their programming knowledge with advanced SAS programming techniques in data access, data manipulation, data management, and data presentation. Topics include data access including reading and writing data and results from tab-delimited, comma separated value (CSV) and MS-Excel spreadsheets and files; control the flow of data in the input buffer and program data vector (PDV); create and apply user-defined formats and functions to dynamically assign values; specify efficient conditional logic scenarios; process columns and rows of data with the DATA step ARRAY statement to process one-dimensional and multi-dimensional arrays; DATA step hash object programming techniques to leverage available memory resources; search, match, merge, and join tables of data using fuzzy matching programming techniques; create simple and composite indexes to dynamically access data; and data-driven programming techniques.

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Advanced DATA Step Programming Techniques
Josh Horstman
Friday, November 15, 2024, 1:00 PM - 5:00 PM

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 function 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.

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Automate Manual Excel and PDF Report Creation with Dynamic SAS® Code Your newest BFF (Best Friend Forever) in SAS
Kent Phelps
Friday, November 15, 2024, 1:00 PM - 5:00 PM

This half-day training course will teach you how to automate your manual Excel and PDF creations with dynamic SAS® code. You will learn how to transform static code into dynamic code that automatically re-creates the static code, and then executes the re-created static code automatically. This course highlights the powerful partnership that occurs when dynamic code is creatively combined with the SASFILE statement, SAS Templates, Excel Templates, Macro variables, ODS Output Delivery System, Excel, PDF, and the CALL EXECUTE command to automatically create tens, hundreds, and even thousands of manual Excel or PDF Reports in minutes – rather than hours, days, and months! You will also have the exciting opportunity to learn how to automatically create an Excel Pivot Table within each Excel Report. This course details the UNIX and Microsoft Windows syntax for the project example and introduces you to your newest BFF (Best Friend Forever) in SAS.

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PROC SQL Programming Masterclass Using SAS®
Kirk Paul Lafler
Friday, November 15, 2024, 1:00 PM - 5:00 PM

PROC SQL Programming Masterclass Using SAS® provides attendees with core concepts, features, and coding techniques on how to effectively use PROC SQL. Attendees learn how to use PROC SQL to access and retrieve data in SAS datasets (tables); essential programming tasks including specifying SELECT statement clauses (i.e., FROM, INTO, WHERE, ON, GROUP BY, HAVING, ORDER BY); execution order of the SELECT clauses; subsetting data with WHERE, ON and HAVING, ordering data and results with ORDER BY, and grouping data with GROUP BY and HAVING; constructing logic scenarios using case expressions; exploring one-to-one, one-to-many, and many-to-many data relationships; creating inner and outer join constructs (i.e., inner and outer - left, right, and full) as well as the application of set operators to combine two or more tables together; using summary (statistical) functions to aggregate data; creating new tables using three different approaches; interfacing PROC SQL and the macro facility to create single-value (aggregate) and multi-value (list) macro variables; the strategies and techniques related to the design and implementation of simple and composite indexes; the application of query debugging techniques to help detect coding errors, warnings, and other issues; and the application of efficient SQL queries (scaling) for improved performance.

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From %MACRO to %MEND: Getting Started with SAS Macro Language Basics
Josh Horstman
Saturday, November 16, 2024, 8:00 AM - 5:00 PM

This full-day seminar is designed for the SAS programmer who is new to the Macro Language. We will start with the basics and cover the fundamentals necessary to start applying SAS macros in your programs. By the end of the course you will understand how the Macro Language works, what the Macro Symbol Table is and how to store values in it, how the SAS System uses Macro Variables, key Macro Language concepts, important SAS Macro Language statements, and how to invoke Macros in your programs. The examples shown in the course materials demonstrate the power and flexibility of this part of the SAS System and will enable you to apply its functionalities to your own programs right away.

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Joinless Join: The Impossible Dream Come True Using SAS® Enterprise Guide®, PROC SQL, and DATA Step
Kent Phelps
Saturday, November 16, 2024, 8:00 AM - 12:00 PM

SAS® Enterprise Guide® and Base SAS® can easily combine data from tables or data sets by using a PROC SQL Join to match on like columns or by using a DATA Step Merge to match on the same variable name. However, what do you do when tables or data sets do not contain like columns or the same variable name and a Join or Merge cannot be used? You are invited to attend this exciting half-day training course on the Joinless Join where you will be empowered to expand the power of SAS Enterprise Guide and Base SAS in new ways by creatively overcoming the limits of a standard Join or Merge. You will learn how to design a Joinless Join based upon dependencies, indirect relationships, or no relationships at all between the tables or data sets using SAS Enterprise Guide and Base SAS PROC SQL and DATA Step. In addition, you will learn how to use a Joinless Join to prepare unrelated joinless data to be utilized by ODS and PROC REPORT in creating a PDF. Come experience the power and versatility of the Joinless Join to greatly expand your data transformation and analysis toolkit. Welcome to the surprising paradox of the Joinless Join.

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Get Your Report to Excel, PDF, or the Web
LeRoy Bessler
Saturday, November 16, 2024, 8:00 AM - 12:00 PM

Deliver your report in any of the most popular formats. The SAS® Output Delivery System (ODS) supports a variety of output formats, also called “output destinations” in the documentation. Three of them are the ones where most programmers and the viewers of their output go. They are the formats that recipients and seekers of information most frequently encounter and find useful. SAS ODS Excel output lets your recipient reformat the data however desired, or do post-delivery analysis. Excel probably holds most of the world’s data. One of my consulting clients had a corporate standard of requiring all SAS reporting output to be delivered in Excel. ODS Excel permits you to programmatically customize your deliverable, rather than do it manually after export. SAS ODS PDF presents a finished, edit-proof package (or, at least, not editable without special software). SAS ODS HTML5 gives the recipient data tips or mouseover text for graphics, and allows you to interlink report content components, or provide links to anywhere you want to be linkable. When plot points are too dense for annotation or axis tables, data tips are the only recourse to give the viewer correct and certain knowledge. HTML5 is the latest and best version of HTML. An important advantage is that it can imbed all of the web page’s image files. If you need to relocate the web page HTML file, or want to email it, you do not need to also move or attach its image files. All three destinations support hyperlinks, and outputs in any of the formats can link to related output in another of the formats. Learn how to take advantage of these SAS-provided reporting conveniences and courtesies for the recipients of your work product, whether tabular or graphic or text. The only prerequisite is familiarity with SAS basics.

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Programming by Example: Applied Statistical Modeling for Hypothesis Testing Using R
Ryan Paul Lafler
Saturday, November 16, 2024, 8:00 AM - 12:00 PM

This half-day R programming workshop is open to all data scientists, decision scientists, statisticians, researchers, students, educators, clinical trials associates, and programmers interested in conducting applied statistical analysis using the R programming language to answer fundamental questions about populations of interest through parametric and nonparametric statistical models. Attendees will gain valuable skills processing, cleaning, visualizing, and generating descriptive statistics for datasets using the well-supported `tidyverse` ecosystem of packages in R. Statistical models including t-tests; One-Way ANOVA (Analysis of Variance); and Factorial ANOVA are developed in R, including a thorough discussion of each model’s assumptions, use-cases, output, and limitations. Frequently used nonparametric models including Mann-Whitney’s U; Wilcoxon’s Signed-Rank; and Kruskal-Wallis are likewise investigated and developed in R. In addition to these statistical models, attendees are given a rigorous overview of applied statistical analysis that includes parametric and nonparametric statistical models; causation vs. correlation; power analysis; effect sizes; practical vs. statistical significance; error probabilities and analysis mistakes; testing for interaction effects; reporting results for submissions; and the importance of post-hoc analysis when finding statistically significant results. By enrolling in this workshop, attendees receive the PDF-slides, interactive R notebooks containing the documented R code, and the confidence to successfully develop and interpret statistical models using the R programming language in their organizations.

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Create Charts and Plots That Are Quickly Easily Understood
LeRoy Bessler
Saturday, November 16, 2024, 1:00 PM - 5:00 PM

Learn best ways to get beyond the defaults, for 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, your client, or yourself. No prior experience is needed for this course. Visuals are for quick easy inference, but precise numbers are needed for correct reliable inference. Learn all the ways to deliver precise numbers. Free the viewer from estimating where bar end or plot point lands on the axis (axes). Provide certainty, not guesses. That’s only one of the key design principles. Color misuse is a common obstacle to visual communication. Learn how my graphic and color design principles are implemented with widely applicable examples. Learn from what I learned, discovered, and invented over 44 years of effort to get the best out of SAS graphics. See Time Series Plots and Trend Lines, simple or overlaid, including use of uncommon, but powerful, design concepts, for when the familiar and customary is not enough. Categorical Data has so many ways to show itself, and with designs to make it show itself better. For One Categorical Variable: Bar Chart; Dot Plot as horizontal bar chart alternative; Needle Plot as vertical bar chart alternative; Pie Chart, and Donut Chart as a hole-in-the-middle alternative; Text Chart as a surprising but equally communication-effective bar chart alternative. For Two Categorical Variables: Stacked, Clustered, or Overlaid versions of bar charts, dot plots, and needle plots; Butterfly Chart, the bi-directional horizontal bar chart for when the second categorical variable has only two values; Line Chart as on-image second categorical variable companion to a bar chart; Bubble Plot; Heat Map with a Discrete Legend or an Actually USABLE Gradient Legend. ODS Graphics lets you package composites of different graphic views of the same data, or similar graphic views of related data, using PROC SGPANEL, PROC SGSCATTER, or ODS LAYOUT. This is a course for which there is no substitute. It can take you from no experience to proficient at creating charts and plots for quick easy understanding—instant, immediate, unambiguous communication. Resources will be suggested where the student can find additional and more advanced possibilities and capabilities than can be covered in the half-day course.

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Regression Expression! 24 Regression Methods in SAS
David Corliss
Sunday, November 17, 2024, 8:00 AM - 5:00 PM

With so many regression procedures available for different situations, it can be difficult to know the breadth of available methods and how to select the ones to apply to a given problem. This course offers an overview of 24 regression-based methods. A decision flowchart is provided to assist in selecting the most useful regression procedures for a given context. The course is practical and example driven, emphasizing which procedures to consider and how to apply them in real situations. A quick introduction to each method followed by two worked examples, with discussion of use cases, options in the SAS procedures, and producing graphical output. The course begins with a basic overview of linear regression, progressing to more advanced techniques. Course modules include basic regression, procedures for specific data issues and needs (e.g., robust regression for outliers), special model types (e.g., quantile regression), logistic regression methods, and mixed, non-linear, and non-parametric SAS procedures. This course will help discern which statistical methods should be considered in a given situation and provide details with source code and examples for using specific procedures.

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ODS Graphics I: Creating Quick and Easy Graphs with the Statistical Graphics (SG) Procedures
Josh Horstman
Sunday, November 17, 2024, 8:00 AM - 12:00 PM

The ODS Statistical Graphics (SG) Procedures represent a complete paradigm shift for the creation of high-quality graphics using the SAS system. Legacy SAS/GRAPH functions produce crude graphics that frequently do not meet today’s standards of presentation. While customization is possible, it can require extensive coding and several tricks to achieve desirable results. With the introduction of the SG procedures, all of that changed. This course will provide an overview of the major procedures such as SGPLOT, SGPANEL, and SGSCATTER as well as related statements and common options using numerous examples. Upon completion of the course, students will have the tools they need to start producing high-quality graphics and performing basic customization using the options available.

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Favorite FunKey Functions: Functions for Your Programming Toolbox
Richann Watson
Sunday, November 17, 2024, 8:00 AM - 12:00 PM

Functions are an invaluable part of the programmer’s toolbox. While some functions are extremely popular, for good reason, there are some that could be considered hidden gems. This training will highlight less commonly used functions, such as the PRXCHANGE and PRXPARSE functions, which are essential for efficient string manipulation. Another example is the COALESCE(C) function, which can facilitate the population of missing values based on parameters, and more. This course will illustrate through examples these and more FunKey functions. Additionally, this course will explore the utility of writing functions with the FCMP procedure, which combines the reusability of macro processing with the power of functions, and learn to enhance SAS reporting with user-written style functions. The course is designed for everybody of all skill levels.

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CS 301: Issues in Managing Reuse of SAS programs, Datasets and Catalogs
Ron Fehd
Sunday, November 17, 2024, 8:00 AM - 12:00 PM

This course is an overview of SAS software files used at startup and shutdown: endsas. The primary purpose of this course is the discussion of two expectations: centralization and standardization. Major sections are: autoexec.sas, batch processing, command-line interface (cli), configuration files, cli option sysparm (also a macro variable), startup-only options init- and term-statement, and use of SQL dictionaries. Topics include: writing *.bat or *.cmd files with startup-only options; the relationships between environment variables and startup-only options in sasv9.cfg; writing notes to the log with job information: program name and start-datetime in initial-statement.sas; and using SQL to research the global symbol table.

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The SASSY System
David Bosak
Sunday, November 17, 2024, 1:00 PM - 5:00 PM

The SASSY system is a set of R language packages that make programming in R easier for everyone, especially those with a background in SAS®. The packages provide a nearly-automatic logging system, and many functions that mimic ideas from SAS®: a libname, a data step, reuseable formats, and functions that replicate common procedures like PROC FREQ and PROC MEANS. With these packages you will be able to easily replicate the outputs you create in SAS. This will be a hands-on workshop. By the end of the tutorial, you will be doing analysis and writing reports in R much in the same way you do it in SAS®.

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Working with Medicare and Medicaid administrative data sets using BASE SAS programming
Jay Iyengar
Sunday, November 17, 2024, 1:00 PM - 5:00 PM

This training seminar will give attendees an overview of the Medicare and Medicaid programs and a detailed explanation of the different types of Medicare/Medicaid data sets, and the SAS programming constructs to work with them. This includes different data repositories used to access Medicare/Medicaid claims such as the VRDC (Virtual Research Data Center). In addition, attendees will receive a background and in-depth explanation of the Medicare and Medicaid Federal programs. The course features demonstrations using SAS to perform analytic and reporting tasks with healthcare data sets. The course is geared towards SAS programmers and data analysts working for government contractors or research institutions who utilize Medicare and/or Medicaid data.

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Driving Miss Data: Data-Driven Techniques
Richann Watson
Sunday, November 17, 2024, 1:00 PM - 5:00 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!

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Instructor Biographies

David Bosak

David is the Chief Software Architect at Archytas Clinical Solutions, founder of r-sassy.org, and author of the SASSY system. Prior to his current position, he was a consultant to pharma and non-pharma companies for 23 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 has ten R packages published on CRAN.

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Josh Horstman

Joshua Horstman is an independent statistical programming consultant and trainer based in Indianapolis with over 25 years of experience using SAS, primarily in the life sciences industry. Josh is a SAS Certified Advanced Programmer who loves coding and presenting at SAS user group conferences and other industry events. Josh also enjoys travelling and hiking with his family and has been to 47 states and 28 national parks.

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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.

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Kirk Paul Lafler

Kirk Paul Lafler is a consultant, developer, programmer, educator, and data scientist; and teaches SAS Programming and Data Management in the Statistics Department at San Diego State University. Kirk also provides project-based consulting and programming services to client organizations in a variety of industries including healthcare, life sciences, and business; and teaches “virtual” and “live” SAS, SQL, Python, Database Management Systems (DBMS) technologies (e.g., Oracle, SQL-Server, Teradata, MySQL, MongoDB, PostgreSQL, AWS), Excel, R, cloud-based technologies as well as other software and tools. Currently, Kirk serves as the Western Users of SAS Software (WUSS) Executive Committee (EC) Open-Source Advocate and Coordinator and is actively involved with several proprietary and open-source software, DBMS, machine learning, cloud-computing user groups and conference committees. Kirk is the author of several books including the popular PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019), along with other technical books and publications. He is also an Invited speaker, educator, keynote, and leader; and is the recipient of 29 “Best” contributed paper, hands-on workshop (HOW), and poster awards.

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Kent Phelps

Kent and Ronda Team Phelps are The SASketeers: All for SAS and SAS for All! They founded Illuminator Coaching, Inc., as a platform to share the ever-expanding wonders of SAS®. Their background includes 7 Presentations and 4 Hands-On Workshops (Best HOW 2019) at MidWest SAS® Users Group Regional Conferences; an Advanced Presentation and a Presentation Video at SAS® Global Forums; and a Livestream Presentation at the Southeast SAS® Users Group Regional Conference. Kent is a Senior Data, Technical, Business Analyst, Developer, Engineer, Programmer, Trainer, Coach, and Consultant and a SAS® Certified Professional Programmer who has happily programmed in SAS® since 2007. He endeavors to coach, encourage, and equip you to fulfill your life, career, and leadership potential as you build an enduring legacy of inspiration, excellence, and honor. Ronda is a Writer and Coach who previously served in the Banking and Insurance industries. She believes that YOU are a gift the world is waiting to receive and endeavors to coach, encourage, and equip you to pursue your unique destiny as you navigate your life journey with intentionality, fulfilling purpose, and enduring hope.

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LeRoy Bessler

LeRoy Bessler PhD is a data artist, the world’s longest-serving advisor to SAS users on best practices for graphics design and color use, and author of Visual Data Insights Using SAS ODS Graphics: A Guide to Communication-Effective Data Visualization. His principles explained and demonstrated in the book are useful for any graphics software. As a data analyst and SAS software expert, his distinguishing non-graphics expertise with SAS is software-intelligent application development for reliability, reusability, maintainability, extendibility, and flexibility—to deliver Strong Smart Systems™.

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Ron Fehd

Ronald J. Fehd has a B.S. in Computer Science. He has over 35+ years programming experience. His screen name on the SAS-L listserv is macro maven. On www.lexjansen.com, the repository of SAS User Group Proceedings, he is the fourth most published author. His 50+ titles published since 1996 include papers on cardinality ratio, list processing, macro definitions as 'functions' to read lists and call subroutines, scl: source control language, SQL: structured query language, syntax of gotcha statements and functions, theory of programming, issues in program reuse: autoexec.sas, batch processing, and configuration.

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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.

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Richann Watson

Richann Watson is an independent statistical programmer and CDISC consultant based in Ohio who loves to code and is very active in the SAS User Group community. 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.