ucla cs courses
Letter grading.

Recommended: course 111. Individual contract with faculty mentor required. Letter grading. Letter grading. Techniques and examples used in areas such as healthcare, financial systems, commerce, and social networking. Lecture, four hours; outside study, eight hours. UCLA Computer Science 101 Computer science is a branch of engineering that encompasses the design, modeling, analysis, and applications of computer systems.

Letter grading. Requisites: courses M51A, 180. S/U grading. Temporal queries, spatial queries, and uncertainty in deductive databases and object relational databases (ORDBs). Recommended: courses 111, and M152A or Electrical and Computer Engineering M116L. Favorites, recommendations, and notifications are only available for UCLA Graduate Students at this time. Letter grading. Topics include hardware and software platforms for embedded systems, techniques for modeling and specification of system behavior, software organization, real-time operating system scheduling, real-time communication and packet scheduling, low-power battery and energy-aware system design, timing synchronization, fault tolerance and debugging, and techniques for hardware and software architecture optimization.

S/U grading. Current CS Science and Technology (Sci-Tech) Options. Topics include safety, liveness, program and state assertion-based techniques, weakest precondition semantics, Hoare logic, temporal logic, UNITY, and axiomatic semantics for selected parallel languages. May be repeated for credit with topic change. May not be repeated. Number systems: conventional, redundant, signed-digit, and residue. Computer Science Graduate Program at UCLA404 Westwood PlazaEngineering IV, Room 291Box 951596Los Angeles, CA 90095-1596, Visit the Computer Science’s faculty roster, Visit the registrar's site for the Computer Science’s course descriptions. Soundness proofs for static analyses. Lecture, four hours; outside study, eight hours. Recommended: course 161. (Same as Electrical and Computer Engineering M171L.) Formal specification and implementation of variety of static analyses, as well as readings from recent research literature on modern applications of static analysis. Review of Bayesian networks, causal Bayesian networks, and structural equations. P/NP grading.

Selections from design, analysis, optimization, and implementation of algorithms; computational complexity and general theory of algorithms; algorithms for particular application areas. Requisite: course 112 or Electrical Engineering 131A. Topics include noninteractive zero-knowledge proofs; zero-knowledge arguments; concurrent and non-black-box zero-knowledge; IP=PSPACE proof, stronger notions of security for public-key encryption, including chosen-ciphertext security; secure multiparty computation; dealing with dynamic adversary; nonmalleability and composability of secure protocols; software protection; threshold cryptography; identity-based cryptography; private information retrieval; protection against man-in-middle attacks; voting protocols; identification protocols; digital cash schemes; lower bounds on use of cryptographic primitives, software obfuscation. Major emphasis on effective research reporting, both oral and written. Requisite: course 211. Requisite: course 161. Finite-state languages and finite-state automata.

Lecture, four hours; outside study, eight hours. Problem solving in PC laboratory. Lecture, two to four hours; outside study, four to eight hours. Letter grading. Focus on formulating interdisciplinary problems as computational problems and then solving those problems using computational techniques from statistics and computer science. Method of stages. Letter grading. Precursor course to introductory computer science sequence (courses 31, 32, 33). Introduction to cryptography, computer security, and basic concepts and techniques. Project-based course covers applied topics in medical imaging including image processing, atlasing, predictive modeling, personalized medicine, data driven and machine learning methods. Letter grading. Requisite: course 132.

Recommended requisite or corequisite: Mathematics 3C, 32A, or 32T. Letter grading.

Its study at UCLA provides education at the undergraduate and graduate levels necessary to understand, design, implement, and use the software and hardware of digital computers and digital systems. Letter grading. Introduction to current topics in bioinformatics, genomics, and computational genetics and preparation for computational interdisciplinary research in genetics and genomics. Experimental project based on mobile radio-equipped devices (smart phones, tablets, etc.) Dynamic biosystem modeling and computer simulation methods for studying analyzing biological/biomedical processes and systems at multiple levels of organization. May be repeated for credit.

May be repeated for credit with topic change.


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