Building a Large-Scale, Automated Forecasting System

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.

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.