Berkeley Global Computing and Data Science Program: A Forward-Looking Curriculum for a Data-Driven World
The Berkeley Global Computing and Data Science Program offers an immersive academic experience designed to prepare the next generation of data-driven thinkers, computational innovators, and ethical leaders in the era of artificial intelligence. In partnership with the UC Berkeley College of Computing, Data Science, and Society (CDSS), this program blends rigorous academic coursework with global perspectives, hands-on learning, and interdisciplinary inquiry.
Students complete 12-13 units that combine a required seminar, a foundational core course, and two upper-division electives. Together, these components provide a holistic understanding of data science from statistical prediction and machine learning to ethics, AI, and societal impact.
Required Seminar: Special Topics on Computing, Data Science, and Society (CDSS X410)
This cornerstone course, offered through UC Berkeley Extension, examines contemporary issues at the intersection of AI, ethics, and the future of work. Students engage in discussions, case studies, and collaborative projects that challenge them to think critically about how emerging technologies shape society, both the possibilities and the risks.
Core Courses
- DATA C100 – Principles & Techniques of Data Science:
A comprehensive introduction to the data science lifecycle, including data cleaning, visualization, statistical inference, machine learning, and communication. - STAT 154 – Modern Statistical Prediction & Machine Learning:
A rigorous examination of statistical learning theory and machine learning methods, including regression, classification, resampling, and model assessment.
Elective Courses
- Elective 1: Must be an upper-division course from CDSS, allowing deeper exploration of topics such as algorithms, human-centered design, advanced machine learning, information ethics, or computational modeling.
- Elective 2: May come from any UC Berkeley department offering flexibility for students interested in connecting data science with fields like economics, public health, engineering, social sciences, or humanities. UC Berkeley Extension courses may be substituted only in exceptional cases.