Graduate Certificate in Applied Data Science
A Three-Course Certificate for Berkeley Grad Students
Learn the tools, methods, and conceptual approaches that support modern data analysis and decision-making in professional and applied research settings.
The Graduate Certificate in Applied Data Science introduces the tools, methods, and conceptual approaches used to support modern data analysis and decision-making in professional and applied research settings. It exposes students to the challenges of working with data (e.g., asking a good question, inference and causality, decision-making) as well as to the new tools and techniques for data analytics (machine learning, data mining, and more).
The certificate is particularly designed to meet the needs of the graduate students in Berkeley’s professional schools — both professional master’s students and doctoral students — as well as graduate students in the social sciences and the arts & humanities.
A Foundation in Modern Data Analysis
The need for expertise in data analytics continues to grow in all organizations and disciplines. Graduate students in every field are now working with data from new sources: websites, electronic medical records, transaction records, sensor networks, smart phones, and digitized records and documents. The analytical tools and methods traditionally used to derive insights from structured and well-curated data sets (census, surveys, and administrative data) are not sufficient for this new, unstructured and often user-generated data.
The Graduate Certificate in Applied Data Science provides hands-on practice working with unstructured and user-generated data to identify new ways to inform decision-making. The curriculum educates professionals and scholars to be intelligent consumers of data science techniques in a variety of domains, with a foundation of skills for applying these techniques in their own domains.
The certificate requires three 3-unit courses, taken from the approved lists:
An introductory data science class
A course in analytical methods and techniques of data science
An additional elective: either a domain-specific data science course or a second methods course.
Courses must be taken for a letter grade and completed with a grade of B or higher.
Be registered and enrolled in a graduate degree at UC Berkeley
Be in good academic standing
Meet course and subject matter prerequisites for courses taken in the certificate program, typically including Python programming and basic statistics knowledge.
Students may apply at any time during their UC Berkeley graduate career, either before or after taking courses that would count toward the certificate.
Applications are reviewed twice per year, in the middle of the fall and spring semesters. Students who are graduating at the end of Fall 2020 must apply by October 1, 2020.