Graduate Certificate in Data Science at University of Colorado Boulder

Programme overview

The on-campus Master of Science in Data Science program focuses on developing knowledge and skills in interdisciplinary and collaborative data science competencies including statistical analysis, data structures and algorithms, data mining, machine learning, big data architecture and data visualization. The on-campus program offers a stackable graduate certificate that can be earned on its own or applied toward the full master’s degree. Graduates of the certificate and/or full master’s degree program will be well-prepared to apply data science skills to a specific domain area.

Faculty: College of Engineering and Applied Science | Department: Data Science | Duration: 12 credit hours | Location: Boulder, CO, United States

What you will study

Sample listed courses: STAT 5600 Methods in Statistical Learning; CSCI 5622 Machine Learning; STAT 5010 Statistical Methods and Applications II.

Official programme page

Application information

Entry requirements

Initially, the proposed Residential Data Science Graduate Certificate will be primarily for students who meet either of the following criteria: Currently matriculated CU Boulder residential or online (Canvas) graduate student in a participating department on Main Campus. Graduate or non-degree seeking students in other disciplines with an interest in data science. Students are required to have an awarded bachelor's degree to be admitted into the residential Data Science or Online (Canvas) Graduate Certificate and will be subject to graduate main campus graduate certificate policies for admission/award. Further admission requirements and processes will be refined by the Data Science Faculty Director and oversight committee.

Tuition is charged per credit, so the total depends on the modules you register for each year. Current fees are listed in the official fee schedule.

Duration: 12 credit hours

Apply through the official page: https://www.colorado.edu/graduateschool/admissions

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