Predictive Modeling with Logistic Regression using SAS

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.

Predictive Modeling with Logistic Regression using SAS is a non-degree program that teaches you predictive modeling skills. It's an online program that lasts several weeks and is taught in English. You'll learn from experts at Statistical Analysis System (SAS) in California.

In this program, you'll learn about logistic regression and predictive modeling using SAS. You'll develop skills in data modeling, statistical analysis, and data interpretation. The program includes practical exercises to help you apply your knowledge.

After completing this program, you can work as a Data Scientist, Statistical Analyst, or Marketing Analyst. You can also work as a Credit Risk Analyst or a Forecasting Analyst. These jobs are available in industries like finance, marketing, and healthcare, and employers like banks, marketing firms, and hospitals.