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Course Criteria
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1.00 - 12.00 Credits
Internship-3-36 hours; term paper. Prerequisite: junior or senior standing; availability of internship position or approved field work project; stock-brokerage interns must have completed Management 11A-11B; consent of instructor. Intensive study of practical application of concepts in economics, stressing research methods and empirical analysis. (P/NP grading only.)
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1.00 - 5.00 Credits
Prerequisite: consent of instructor. Primarily for lower division students. (P/NP grading only.)
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1.00 - 5.00 Credits
Prerequisite: consent of instructor. (P/NP grading only.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:two years of high school algebra. Introduction to principles of computing. Methods and algorithms for solving problems by use of a digital computer. Not open for credit to students who have completed course 30 or Engineering 6.-I, II, III. (I, II, III.) Amenta, Ludaescher, Gertz
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 20; Mathematics 108 recommended. Fundamental ideas in the theory of computation, including formal languages, computability and complexity. Reducibility among computational problems.-I, II, III. (I, II, III.) Bai, Franklin, Gusfield, Rogaway, Martel
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:courses 20, 60. Complexity of algorithms, bounds on complexity, algorithms for searching, sorting, pattern matching, graph manipulation, combinatorial problems, randomized algorithms, introduction to NP-complete problems.-I, II, III. (I, II, III.) Gusfield, Martel, Rogaway
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 122A. Theory and practice of hard problems, and problems with complex algorithm solutions. NP-completeness, approximation algorithms, randomized algorithms, dynamic programming and branch and bound. Students do theoretical analysis, implementation and practical evaluations. Examples from parallel, string, graph, and geometric algorithms.- I. (I.) Rogaway, Gusfield, Martel
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4.00 Credits
Lecture-3 hours; laboratory-1 hour. Prerequisite:course 10 or 30 or Engineering 6; Statistics 12 or 13 or 32 or 100 or 131A or Mathematics 135A; Biological Science 1A or Molecular and Cellular Biology 10. Fundamental biological, mathematical and algorithmic models underlying bioinformatics; sequence analysis, database search, gene prediction, molecular structure comparison and prediction, phylogenetic trees, high throughput biology, massive datasets; applications in molecular biology and genetics; use and extension of common bioinformatics tools.-III. (III.) Filkov, Gusfield
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:college level programming course; Biological Science 1A or Molecular and Cellular Biology 10. Fundamental biological, chemical and algorithmic models underlying computational structural biology; protein structure and nucleic acids structure; comparison of protein structures; protein structure prediction; molecular simulations; databases and online services in computational structural biology.-I. (I.) Koehl
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 30 or Engineering 6; Mathematics 22A. Matrix-vector approach using MATLAB for floating point arithmetics, error analysis, interpolations, numerical integration, matrix computations, nonlinear equations and optimization. Parallel computing for matrix multiplication and the Cholesky factorization.- III. (III.) Bai
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