Building a Large-Scale, Automated Forecasting System

Statistical Analysis System, widely known as SAS, is a leading analytics and AI software company established in 1976 that supports organizations across healthcare, finance, government, and academia. While not a traditional university, SAS plays a major educational role through its analytics platforms, research collaborations, and partnerships with colleges and universities. Its tools are used for statistical analysis, predictive modeling, machine learning, and enterprise intelligence.

For international students pursuing data science, analytics, or related fields, SAS offers a range of learning pathways including certification programs, instructor-led courses, online training, and academic alliances with more than 40 program tracks and learning modules. These resources are designed to develop practical skills in real-world problem solving, from data preparation and visualization to advanced modeling and deployment. Students can access hands-on labs, community forums, and sanctioned curricula that align with industry expectations.

Engagement with SAS technologies can significantly enhance employability in a competitive job market where analytics expertise is in demand. Prospective learners should explore university partnerships, internship opportunities, and certification routes that complement degree programs. International applicants can benefit from SAS learning resources to build portfolios, demonstrate technical competence to employers, and transition more smoothly into analytics roles globally.

Building a Large-Scale, Automated Forecasting System is a non-degree program for students who want to learn about forecasting. It's taught in English and lasts several weeks. The main advantage is that it's online and flexible.

The curriculum covers forecasting methods and automated system design. Students learn to work with large datasets and develop skills in data modeling and system implementation. They also get hands-on experience with forecasting tools and techniques.

After completing this program, students can pursue careers as Forecasting Analysts, Data Engineers, Quantitative Analysts, or Business Forecasters. They can work in various industries, including finance and retail, for employers like consulting firms and government agencies.