Statistical Learning for Data Science 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 Learning for Data Science Specialization is a non-degree program for those pursuing a career in data science. It's offered by the University of Colorado Boulder and takes place online. This program helps you build on your foundational knowledge of statistics and equips you with advanced techniques.

The curriculum covers model selection, regression, classification, trees, SVM, unsupervised learning, splines, and resampling methods. You'll gain an in-depth understanding of coefficient estimation and interpretation, which will help you explain and justify your models to clients and companies. You'll also develop conceptual knowledge and communication skills to effectively convey the rationale behind your model choices and coefficient interpretations.

After completing this program, you can pursue careers such as Data Scientist, Business Analyst, Quantitative Analyst, Operations Research Analyst, or Statistical Analyst. You can work in various industries, including finance, healthcare, and technology, and for employers like IBM, Microsoft, or Google.