About SAS

Ari Zitin is a Senior Analytical Training Consultant at SAS, where he specializes in teaching advanced analytical techniques and the effective use of SAS software for data analysis. He holds bachelor's degrees in both physics and mathematics from the University of North Carolina at Chapel Hill, where his research focused on low-energy physics data related to neutrinos. Zitin has also taught introductory and advanced physics courses at UC Berkeley while pursuing a master's degree in physics with a focus on nonlinear dynamics. At SAS, he has developed courses that integrate Python programming with SAS analytical procedures, enhancing the learning experience for users. His expertise extends to conducting workshops on machine learning and model interpretability, helping participants understand complex analytical models and their applications. Through his work, Zitin is committed to empowering individuals and organizations to leverage data-driven insights for informed decision-making.

Dr. Chip Wells serves as Senior Manager of Analytical Education at SAS Institute, bringing over three decades of experience in statistical analysis and forecasting since joining SAS in 1991. With a Ph.D. in Economics from North Carolina State University, he specializes in SAS Forecast Server, Enterprise Miner, Model Manager, and advanced statistical tools. His expertise spans time series analysis, predictive modeling, and automated forecasting systems. Through his Coursera courses "Building a Large-Scale, Automated Forecasting System," "Creating Features for Time Series Data," and "Modeling Time Series and Sequential Data," he shares his extensive knowledge in forecasting and time series analytics. His contributions include co-authoring "Applied Data Mining for Forecasting Using SAS," which provides practical guidance for practitioners in selecting and analyzing time series variables. His teaching focuses on helping professionals develop practical skills in building and implementing large-scale forecasting systems while understanding the theoretical foundations of time series analysis.

Danny Modlin serves as Senior Analytical Training Consultant at SAS, bringing unique expertise in spatial Bayesian environmental statistics and educational technology. His academic background includes advanced studies at NC State University, where his research focused on hurricane forecasting and wind modeling. Prior to joining SAS, he spent six years teaching mathematics and computer science in secondary education before pursuing graduate studies in statistics. Through his Coursera course "Modeling Time Series and Sequential Data," he shares his expertise in statistical analysis and forecasting methodologies. His work at SAS includes teaching advanced analytics courses and developing training materials for statistical concepts and SAS software applications. His specialties include Bayesian analysis, categorical data analysis, and logistic regression, with particular emphasis on making complex statistical concepts accessible to diverse audiences. Currently leading training initiatives for SAS Visual Statistics in SAS Viya, he continues to bridge the gap between theoretical statistics and practical applications in business analytics.

Dr. Emily Pressman serves as Senior Academic Program Manager at SAS, bringing over 16 years of experience in STEM education and curriculum development. After earning her Ph.D. in Education from UCLA, she has dedicated her career to making data literacy accessible to diverse audiences. As the developer of the SAS Data Literacy series, she has created comprehensive educational programs that have reached learners in nearly 80 countries across 600 colleges and universities. Her courses "Data Literacy Essentials" and "Data Literacy in Practice" have been activated over 20,000 times, helping professionals and students develop crucial data skills for the AI-driven world. Her teaching approach emphasizes practical understanding over technical jargon, making data concepts accessible to learners at all levels. Prior to SAS, she held positions at UCLA and the North Carolina Department of Natural and Cultural Resources, contributing to her broad perspective on educational technology and information science. Her work focuses on bridging the gap between technical data skills and practical application, particularly in preparing learners for an increasingly data-driven workforce.

Jay Laramore serves as Senior Analytical Training Consultant at SAS, specializing in econometrics, time series forecasting, and optimization. His expertise combines academic training in economics with extensive practical experience in analytical consulting. Through his Coursera course "Building a Large-Scale, Automated Forecasting System," he shares insights gained from years of implementing forecasting solutions across various industries. His work focuses on developing and teaching advanced analytical methodologies, particularly in automated forecasting systems and time series analysis. His teaching approach emphasizes practical applications, helping professionals master complex forecasting techniques and system optimization. Drawing from his experience in SAS's analytical consulting division, he provides valuable insights into building and deploying large-scale forecasting solutions. His expertise spans automatic model selection, custom model development, and event variable creation, making him a trusted authority in time series analytics and forecasting systems

Marc Huber serves as Senior Analytical Training Consultant at SAS Institute, bringing extensive experience in biostatistics and quantitative psychology. His academic credentials include BA and MA degrees in Quantitative Psychology and an MSW from the University of North Carolina at Chapel Hill. With 14 years of experience as a health researcher in biostatistics and epidemiology at Duke University Medical Center and UNC-Chapel Hill, he brings deep expertise in healthcare analytics. Since joining SAS as an instructor in 2004, he has developed expertise in predictive modeling and forecasting systems. Through his Coursera courses "Building a Large-Scale, Automated Forecasting System" and "Predictive Modeling with Logistic Regression using SAS," he helps professionals master advanced analytical techniques. His teaching approach combines theoretical rigor with practical applications, drawing from his extensive experience in healthcare research and statistical analysis.

Dr. Jordan Bakerman serves as an Analytical Training Consultant at SAS, where he specializes in bridging open-source and SAS analytics platforms. His Ph.D. research at North Carolina State University focused on leveraging social media data to forecast real-world events, including civil unrest and influenza rates. As the creator of the widely-used "SAS Programming for R Users" course, he developed an innovative cookbook-style approach to help R programmers transition efficiently to SAS. His teaching portfolio includes courses on statistical analysis, regression modeling, and API integration between SAS Viya and open-source platforms. Through his Coursera courses "Introduction to Statistical Analysis: Hypothesis Testing," "Regression Modeling Fundamentals," and "Using SAS Viya REST APIs with Python and R," he shares his expertise in statistical programming and analysis. His work focuses on making advanced statistical concepts accessible while helping professionals integrate open-source tools with SAS technologies.

Michele Ensor serves as a Senior Technical Training Consultant at SAS, specializing in advanced SAS programming techniques and certification preparation. Through her highly-rated Coursera course "Advanced SAS Programming Techniques," which has enrolled over 4,000 learners, she helps professionals master complex DATA step processing, advanced functions, arrays, and hash objects. Her teaching effectiveness is demonstrated by her exceptional 4.8/5 instructor rating, reflecting her ability to make complex programming concepts accessible to learners. Her course structure emphasizes practical applications through hands-on assignments and real-world examples, preparing students for the SAS Advanced Programmer certification. Her expertise spans utility procedures, custom functions, and advanced data manipulation techniques, making her a valuable contributor to SAS's educational initiatives.

Nicole Ball serves as Principal Technical Training Consultant at SAS, specializing in SAS Visual Analytics and advanced reporting techniques. Her expertise spans data visualization, geographic mapping, network analysis, and forecasting methodologies. Through her comprehensive Coursera course series, including "Getting Started with SAS Visual Analytics," "Creating Advanced Reports," and "Using Data for Geographic Mapping and Forecasting," she helps professionals master the full spectrum of visual analytics capabilities. Her teaching portfolio includes specialized courses in network, path, and text analyses, demonstrating her broad expertise in advanced analytical techniques. As a key contributor to SAS's educational initiatives, she develops curriculum that bridges the gap between basic reporting and advanced analytics applications. Her courses emphasize practical skills development, helping professionals create impactful visual presentations of complex data while mastering advanced features of SAS Visual Analytics. Her teaching methodology combines theoretical understanding with hands-on experience, enabling learners to develop sophisticated reporting and analysis capabilities.

Peter Styliadis is a Senior Technical Training Consultant at SAS, where he specializes in developing and delivering comprehensive training programs focused on data analytics and visualization. With a strong foundation in programming languages such as SQL, Python, and SAS, Peter has designed and implemented courses that empower users to effectively process and analyze large datasets. His expertise includes leading curriculum development for key courses like SAS SQL Essentials and Data Visualization Using SAS ODS Graphics. In addition to his instructional roles, he actively mentors fellow instructors and collaborates with internal teams to address customer inquiries, leveraging his extensive knowledge of SAS software. Peter's commitment to education is further demonstrated through his involvement in online learning platforms, where he teaches courses that enhance analytical skills for professionals across various industries. Through his innovative training approaches, he plays a vital role in equipping individuals with the tools necessary to harness the power of data for informed decision-making.