Regression Modeling Fundamentals

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.

The Regression Modeling Fundamentals program is a non-degree course that teaches you about regression modeling. It's a short online program that lasts a few weeks and is taught in English. The Statistical Analysis System (SAS) in California offers this program to students who want to learn data analysis.

In this program, you'll learn about specific topics like linear regression, logistic regression, and model evaluation. You'll also develop skills like data modeling, statistical analysis, and problem-solving. The program includes hands-on practice with real data and case studies.

After completing this program, you can work as a Statistical Analyst, Data Scientist, or Quantitative Analyst. You can also work in industries like finance, economics, or social sciences, and companies like research firms, government agencies, or universities may hire you.