Degree Programs in Data Science Fields
UC Berkeley's data science research activities are coupled to a commitment to bring data science into the educational program. The campus has already established several new courses and degree programs aimed at training a new generation of data scientists. The campus is launching four new data science-inflected graduate degrees in 2012 and 2013 that include a Masters Degree in Data Science at the School of Information, a professional Masters Degree in Engineering with a concentration in Data Intensive Systems in Computer Science, a Ph.D. in Computational Biology, and a one-year Masters Degree program in Statistics emphasizing data science. In addition, UC Berkeley is embedded in the Bay Area innovation ecosystem and has strong connections to partners in higher education, industry, and public service. The university’s leadership is committed to UC Berkeley’s pivotal role in the data science field and has devoted significant resources to support these efforts.
- Master of Engineering with a concentration in Data Science and Systems
- Master of Information and Data Science
- Master of Statistics
The Master of Engineering (M.Eng) is a professional masters designed for students who plan to join the engineering profession immediately following graduation. This accelerated program is designed to develop professional engineering leaders of the future who understand the technical, economic, and social issues of technology. This one-academic year interdisciplinary experience includes three major components: an area of technical concentration, courses in leadership skills, and a rigorous capstone project experience. The concentration in Data Science and Systems prepares students for engineering careers in data-centric industries requiring understanding of data management fundamentals as well as the latest technologies and techniques for the collection, storage, and analysis of information. Read more.
Berkeley’s School of Information (I School) will offer the first fully online Master of Information and Data Science degree program, beginning in January 2014. Students will participate in live, face-to-face classes with fellow students and professors via the Web. Classes are small, with no more than 15-20 students. Additional coursework will include lectures, interactive case studies, and collaborative assignments. Classes will use 2U, Inc.’s online platform featuring high-quality I School faculty developed self-paced content and a state-of-the art learning management system.
I School faculty will teach their curriculum alongside experienced data science professionals. Classes will range from an introduction to machine learning (the intersection of computer science and statistics that focuses on finding patterns in data) and data storage and retrieval to the privacy, security, and ethics of data. Read more.
The MA program in Statistics is designed to prepare students for careers in industries that require statistical skills. The focus is on tackling statistical challenges encountered by industry rather than preparing for a PhD. The program is for full-time students and is designed to be completed in two semesters (fall and spring). In order to obtain the MA in Statistics, admitted students must complete a minimum of 24 units of courses and pass a comprehensive examination. In the first semester, all students will take intensive graduate courses in probability, theoretical statistics, and statistical computing. In the second semester, students will take an advanced course in modern applied statistics, an elective, and a capstone course. Read more.
The Computational Biology Ph.D. at UC Berkeley will train the next generation of scientists who are interested in exploring the interface of computation and biology, and committed to functioning at a high level in both computational and biological fields. The program emphasizes multidisciplinary competency, interdisciplinary collaboration, and transdisciplinary research, and offers an integrated and customizable curriculum that consists of two semesters of didactic course work tailored to each student’s background and interests, research rotations with faculty mentors spanning computational biology’s core disciplines, and dissertation research jointly supervised by computational and biological faculty mentors. Read more.
The Electrical Engineering and Computer Sciences (EECS) Department offers a Ph.D. degree in Computer Science. The principal requirements for the Ph.D. are (I) coursework (a major field and two minor fields), (II) departmental preliminary requirement (oral exam and breadth courses) which are different for EE and CS, (III) the qualifying exam, and (IV) the dissertation. The EECS Department requires that a student establish a major subject area and two minor subject areas. The median time of completion for the Ph.D. is five and a half years. Read more.
The Statistics PhD program at UC Berkeley is rigorous, yet welcoming to students with interdisciplinary interests and different levels of preparation. The program requires four semesters of residence. Read more.
This Designated Emphasis is intended for Ph.D. students who seek to focus on the mathematical, statistical and computational techniques, to help them solve Computational Science and Engineering (CSE) problems across a wide range of disciplines. The CSE program actively supports the training and multidisciplinary education of scientists, engineers and technical specialists who are experts in relevant areas. Read more
UC Berkeley construes computer science broadly to include complexity theory, the design and analysis of algorithms, machine architecture and logic design, digital devices and circuits, programming systems and languages, operating systems, computer graphics, database systems, and artificial intelligence. The goal is to prepare students both for a possible research career and long-term technical leadership in industry. The B.A. in Computer Science at UC Berkeley is for students enrolled in the College of Letters & Science (L&S). There is no difference in the computer science course content between the B.S. and B.A. programs. The difference is in what else you take: mainly engineering, or mainly humanities and social sciences. In particular, an interest in hardware suggests the EECS route; an interest in double majoring (for example, in math or cognitive science) suggests the L&S route. Read more.
The undergraduate major in Statistics at UC Berkeley provides a systematic and thorough grounding in applied and theoretical statistics, and in probability. A major in Statistics from Berkeley is an excellent preparation for a career in science, in industry, or as a preparation for further academic study in a wide variety of fields. Read more.
UC Berkeley's B.S. degree in Computer Science and Engineering (CSE) is offered through the College of Engineering (COE). It combines fundamentals of computer science and electrical engineering in one major. Students working for the B.S. degree select an option within their program and are then assigned an appropriate advisor on the basis of their selection. Read more.