Statistical Modeling for Data Science Applications 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.

The Statistical Modeling for Data Science Applications Specialization is a non-degree program for learners who want to improve their data science skills. It's a 3-credit sequence that takes several weeks to complete and is taught in English. The main advantage of this program is that it helps learners become proficient in statistical modeling techniques.

This program covers specific subjects like linear regression analysis, ANOVA, and generalized linear models. Learners will develop skills in data analysis and interpretation using the R programming language. The program also includes hands-on components where learners can practice analyzing real data.

After completing this program, learners can pursue careers like Data Analyst, Business Intelligence Developer, Quantitative Analyst, or Operations Research Analyst. They can work in various industries such as finance, healthcare, or technology, and can be employed by companies like Google, Microsoft, or IBM.