Building a Large-Scale, Automated Forecasting System
Master SAS Visual Forecasting for large-scale projects, from data prep to model selection. Perfect for analysts seeking advanced time series skills.
Master SAS Visual Forecasting for large-scale projects, from data prep to model selection. Perfect for analysts seeking advanced time series skills.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Analyzing Time Series and Sequential Data Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
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What you'll learn
Master automated time series forecasting techniques
Develop custom forecasting models
Implement event variable analysis
Optimize model selection processes
Perform statistical forecast reconciliation
Manage large-scale forecasting systems
Skills you'll gain
This course includes:
3.2 Hours PreRecorded video
19 assignments
Access on Mobile, Desktop
FullTime access
Shareable certificate
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There are 10 modules in this course
This comprehensive course teaches analysts to develop and maintain large-scale forecasting projects using SAS Visual Forecasting tools. Students learn to select appropriate methods for data creation, variable transformations, model generation, and model selection. The course emphasizes improving baseline forecasting performance by modifying default processes, with hands-on practice in creating and implementing custom models, event variables, and forecast reconciliation techniques.
Specialization Overview
Module 1 · 11 Minutes to complete
Course Overview
Module 2 · 30 Minutes to complete
Introduction to Large-Scale Forecasting
Module 3 · 21 Minutes to complete
Exploring and Processing Timestamped Data
Module 4 · 2 Hours to complete
Creating Custom Models and Lists
Module 6 · 59 Minutes to complete
Event Variables in Forecasting
Module 7 · 2 Hours to complete
Reconciling Statistical Forecasts
Module 8 · 1 Hours to complete
Setting Up Forecasting System
Module 9 · 1 Hours to complete
Course Review
Module 10 · 3 Minutes to complete
Fee Structure
Instructors
Time Series Analytics Expert and Forecasting Specialist
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.
Time Series Analytics Expert and Forecasting Systems Specialis
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
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