Performing Network, Path, and Text Analyses in SAS Visual Analytics

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 Performing Network, Path, and Text Analyses in SAS Visual Analytics program is for students who want to learn how to analyze complex data. This non-degree program is taught in English and can be completed online in a few weeks. It helps students learn how to work with network, path, and text data.

The program teaches students about network analysis, path analysis, and text analysis using SAS Visual Analytics. Students learn how to identify patterns, create models, and use data to make predictions. The program includes hands-on exercises to help students practice their skills.

After completing this program, students can work as Network Analysts, Data Scientists, or Text Analysts. They can work in industries like social media monitoring, customer service, or market research. Employers like technology companies, research firms, or financial institutions may hire them.