The Law School approves courses from the Department of Computer Science that may count toward the J.D. degree, and the Computer Science Department approves courses from the Law School that may count toward the M.S. degree in Computer Science. In either case, approval may consist of a list applicable to all joint-degree students or may be tailored to each individual student program. No more than 45 units of approved courses may be counted toward both degrees. No more than 36 units of courses that originate outside the Law School may count toward the Law degree. To the extent that courses under this joint degree program originate outside of the Law School but count toward the Law degree, the Law School credits permitted under Section 17(1) of the Law School Regulations shall be reduced on a unit-per-unit basis, but not below zero. The maximum number of Law School credits that may be counted toward the M.S. in Computer Science is the greater of: (i) 12 units; or (ii) the maximum number of units from courses outside of the department that M.S. candidates in Computer Science are permitted to count toward the M.S. in the case of a particular student's individual program. Tuition and financial aid arrangements are normally through the school in which the student is then enrolled.
J.D./M.S. students may elect to begin their course of study in either the Law School or the Computer Science Department. Faculty advisors from each academic unit participate in the planning and supervising of the student's joint program. Students must be enrolled full-time in the Law School for the first year of law studies. Otherwise, enrollment may be in the graduate school or the Law School, and students may choose courses from either program regardless of where enrolled. Students must satisfy the requirements for both the J.D. degree as specified by the Law School and the M.S. degree as specified in this Bulletin.
This course provides a mathematical introduction to the following questions: What is computation? Given a computational model, what problems can we hope to solve in principle with this model? Besides those solvable in principle, what problems can we hope to efficiently solve? In many cases we can give completely rigorous answers; in other cases, these questions have become major open problems in computer science and mathematics. By the end of this course, students will be able to classify computational problems in terms of their computational complexity (Is the problem regular? Not regular? Decidable? Recognizable? Neither? Solvable in P? NP-complete? PSPACE-complete?, etc.). Students will gain a deeper appreciation for some of the fundamental issues in computing that are independent of trends of technology, such as the Church-Turing Thesis and the P versus NP problem. Prerequisites: or 103B.
Topics include: counting and combinatorics, random variables, conditional probability, independence, distributions, expectation, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of or or equivalent.
Supplemental lab to and . Students will apply fundamental computer science concepts learned in 106B/X to problems in the social good space (such as health, government, education, and environment). Course consists of in-class activities designed by local tech companies and nonprofits. Corequisite: 106B or 106X.
The Department provides facilities for students to pursue programmes of research leading to the MPhil and PhD degrees of the University of London, by both full-time and part-time study. There are two dedicated research labs in the department and a seminar/meeting room for researchers. Part-time PhD students have the use of a number of hot desks with computing facilities. The computer facilities include high performance/throughput computer clusters.
The minimum entry qualification is normally a Masters or upper second class honours degree in Computer Science. The MRes in Computer Science and MRes in Information Systems and Management programmes also provide the necessary foundations for continuing into the MPhil/PhD programme. The period of full-time study for a PhD is normally 3 years, and for part-time study 6 years. For an MPhil it is normally 2 years full-time and 4 years part-time. Students wishing to pursue a PhD degree are first registered for an MPhil or, if appropriate, the MRes. The first 9 months of study (18 months for part-time students) are spent on training in research methods, background research, developing experimental software and exploring possible research directions. After this initial period, a work programme for the remaining period of study is formulated together with supervisors which will lead to a proposed thesis topic. If during the subsequent phase it seems likely that the thesis will contain significant original work, the registration is transferred from MPhil to that of PhD. This normally happens after about 18 months of full-time study (33 months for part-time students).
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Age: 27 Degrees: L. Niversity of Michigan Law School, (expected) 2017; J. University of California, Davis, 2016; B. In Political Science, University of. m phil computer science thesis data mining
“After successful completion of degree in Computer Science, student masters the problem-solving techniques, computer applications, ready to work in IT sectors, pursue higher studies.”
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