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Course Criteria
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1.00 Credits
(Same as Biomedical Engineering CM186C and Computational and Systems Biology M186C.) Lecture, one hour; discussion, two hours; laboratory, one hour; outside study, eight hours. Requisite: course CM186B. Closely directed, interactive, and real research experience in active quantitative systems biology research laboratory. Direction on how to focus on topics of current interest in scientific community, appropriate to student interests and capabilities. Critiques of oral presentations and written progress reports explain how to proceed with search for research results. Major emphasis on effective research reporting, both oral and written. Concurrently scheduled with course CM286C. Letter grading.
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1.00 Credits
Seminar, one hour; discussion, one hour. Introduction to department resources and principal topics and key ideas in computer science and computer engineering. Assignments given to bolster independent study and writing skills. Letter grading. 2. Great Ideas in Computer Science. (4) Lecture, four hours; outside study, eight hours. Broad coverage for liberal arts and social sciences students of computer science theory, technology, and implications, including artificial and neural machine intelligence, computability limits, virtual reality, cellular automata, artificial life, programming languages survey, and philosophical and societal implications. P/NP or letter grading.
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1.00 Credits
Seminar, one hour; discussion, one hour. Introduction to current research, trends, emerging areas, and contemporary issues in computer science and engineering. Assignments given to bolster independent study and writing skills. Letter grading.
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4.00 Credits
Lecture, four hours; laboratory, two hours; outside study, six hours. Requisites: courses 32, 33. Recommended: course 35L. Introduction to operating systems design and evaluation. Computer software systems performance, robustness, and functionality. Kernel structure, bootstrapping, input/output (I/O) devices and interrupts. Processes and threads; address spaces, memory management, and virtual memory. Scheduling, synchronization. File systems: layout, performance, robustness. Distributed systems: networking, remote procedure call (RPC), asynchronous RPC, distributed file systems, transactions. Protection and security. Exercises involving applications using, and internals of, real-world operating systems. Letter grading.
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4.00 Credits
Lecture, four hours; outside study, eight hours. Requisite: Statistics 110A. Designed for juniors/seniors. Probability and stochastic process models as applied in computer science. Basic methodological tools include random variables, conditional probability, expectation and higher moments, Bayes theorem, Markov chains. Applications include probabilistic algorithms, evidential reasoning, analysis of algorithms and data structures, reliability, communication protocol and queueing models. Letter grading.
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4.00 Credits
Lecture, four hours; laboratory, four hours; outside study, four hours. Requisites: courses 111, 118. Introduction to basic concepts needed to understand, design, and implement wireless distributed embedded systems. Topics include design implications of energy and otherwise resource-constrained nodes, network self-configuration and adaptation, localization and time synchronization, applications, and usage issues such as human interfaces, safety, and security. Heavily project based. Letter grading.
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4.00 Credits
Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: courses 32, 33. Highly recommended: course 111. Designed for juniors/seniors. Introduction to design and performance evaluation of computer networks, including such topics as what protocols are, layered network architecture, Internet protocol architecture, network applications, transport protocols, routing algorithms and protocols, internetworking, congestion control, and link layer protocols including Ethernet and wireless channels. Letter grading.
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4.00 Credits
Lecture, four hours; laboratory, two hours; outside study, six hours. Requisite: course 32. Recommended: course 35L, and Engineering 183 or 185. Structured programming, program specification, program proving, modularity, abstract data types, composite design, software tools, software control systems, program testing, team programming. Letter grading.
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4.00 Credits
Lecture, four hours; laboratory, two hours; outside study, six hours. Requisites: courses 32, 33. Recommended: course 35L. Basic concepts in design and use of programming languages, including abstraction, modularity, control mechanisms, types, declarations, syntax, and semantics. Study of several different language paradigms, including functional, object-oriented, and logic programming. Letter grading.
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4.00 Credits
Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: courses 32, 131, 181. Recommended: course 35L. Compiler structure; lexical and syntactic analysis; semantic analysis and code generation; theory of parsing. Letter grading.
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