Machine Learning Using SAS Viya

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.

Machine Learning Using SAS Viya is a non-degree program for students who want to learn machine learning. It's taught in English and lasts several weeks. You'll get to learn from experts at Statistical Analysis System (SAS) in California.

In this program, you'll study machine learning concepts and learn to use SAS Viya. You'll develop skills in data analysis and modeling. The program includes hands-on exercises to help you practice your new skills.

After completing this program, you can work as a Data Analyst, Business Intelligence Developer, or Operations Research Analyst. You can also work as a Machine Learning Engineer or a Quantitative Analyst. These jobs are available in industries like finance, healthcare, and technology, and employers like banks, hospitals, and tech companies.