Data Science Foundations: Statistical Inference Specialization

The University of Colorado Boulder, founded in 1876 and set against the Rocky Mountains, is a major research university serving more than 37,000 students with nearly 3,000 international learners. CU Boulder is recognized for academic excellence, expansive research programs and a sustainability-driven campus culture. Students benefit from an array of undergraduate, graduate and professional offerings that encourage innovation across science, engineering, business, arts and humanities.

Research, entrepreneurship and experiential learning are central to the CU Boulder experience, with extensive laboratory facilities, innovation labs and co-op or internship pathways that connect students to industry and civic partners. The university supports cross-disciplinary projects and provides robust advising, career services and student organizations that help translate academic interests into practical outcomes and start-up ventures.

Boulder's outdoor lifestyle and proximity to tech hubs create strong opportunities for networking, recreation and balanced living. International students are supported by dedicated offices for admissions, orientation and visa guidance, making the transition smoother. With a large program portfolio and a campus culture that values sustainability, creativity and collaboration, CU Boulder is well suited to students seeking high-impact research experiences and an active campus community.

This program is a non-degree course for students who want to learn about statistical inference. It is taught in English and lasts several weeks. The main advantage of this program is that it helps students build a strong foundation in probability theory and statistics.

The curriculum covers probability theory, statistics, and statistical theory. Students will learn how to perform fundamental statistical analysis of a data set using the R programming language. They will also gain skills in data analysis and interpretation.

After completing this program, students can pursue careers as data analysts, statistical consultants, or research assistants. They can work in various industries, including finance, healthcare, or technology. Some potential employers include research institutions, government agencies, or private companies like Google or Microsoft.