ucla cs courses

Introduction to operating systems design and evaluation. Letter grading. Query languages. Discussion of current Internet research topics, including latest research results in routing protocols, transport protocols, network measurements, network security protocols, and clean-slate approach to network architecture design. (Same as Mathematics M208B.) P/NP grading. Preparation: knowledge of basic probability theory. Requisite: course 130 or 131 or 161. Introduction to fundamental computer communication concepts underlying and supporting modern networks, with focus on wireless communications and media access layers of network protocol stack. Letter grading. Designed for juniors/seniors.

Probabilities of counterfactuals. Seminar, two hours; outside study, six hours. Lecture, four hours; outside study, eight hours.

(Same as Bioengineering CM187 and Computational and Systems Biology M187.) Lecture, four hours; discussion, two hours.

Designed for engineering students as well as students from biological sciences and medical school.

Concurrently scheduled with course C137A. Letter grading. Letter grading. P/NP or letter grading.
Requisites: courses M51A, 180. Introduction to mathematical modeling and computer simulation of cardiac electrophysiological process.

Introduction to computational approaches in bioinformatics, genomics, and computational genetics and preparation for computational interdisciplinary research in genetics and genomics. Basics of numerical simulation algorithms, with modeling software exercises in class and PC laboratory assignments. Lecture, four hours; laboratory, two hours; outside study, nine hours.

Designed for freshmen/sophomores. Functions, recursion. Designed for students in computer science and related majors who do not have prior programming experience. (Same as Electrical and Computer Engineering M16.) Special topics in computer science for undergraduate students taught on experimental or temporary basis, such as those taught by resident and visiting faculty members. Hands-on experience designing, prototyping, and evaluating new languages, language abstractions, and/or programming environments. Lecture, four hours; outside study, eight hours. On-chip and off-chip communication. Virtualization, networking, profiling, research operating systems.

Letter grading. Recommended requisite: course 180.

Introduction to computational analysis of genetic variation and computational interdisciplinary research in genetics. Mutual exclusion and resource allocation in distributed systems; primitives for parallel computation: specification of parallelism, interprocess communication and synchronization, atomic actions, binary and multiway rendezvous; synchronous and asynchronous languages: CSP, Ada, Linda, Maisie, UC, and others; introduction to parallel program verification. Closely directed, interactive, and real research experience in active quantitative systems biology research laboratory. Designed for graduate computer science and electrical engineering students.

Lecture, four hours; outside study, eight hours. Fundamentals of commonly used software tools and environments, particularly open-source tools to be used in upper-division computer science courses. Specific topics include modeling plants using L-systems, biomechanical simulation and control, behavioral animation, reinforcement and neural-network learning of locomotion, cognitive modeling, artificial animals and humans, human facial animation, and artificial evolution.
May be repeated for credit with topic change. (Same as Chemistry CM160B.) Introduction to computational models of probability and statistical models of relational data. Study of relational representations such as probabilistic databases, relational graphical models, and Markov logic networks, as well as various probabilistic programming languages. Closely directed, interactive, and real research experience in active quantitative systems biology research laboratory. Computer system organization and design, implementation of CPU datapath and control, instruction set design, memory hierarchy (caches, main memory, virtual memory) organization and management, input/output subsystems (bus structures, interrupts, DMA), performance evaluation, pipelined processors. Introduction to methods for modeling and simulation using interactive computing environments. Computational techniques include those from statistics and computer science. Designed for graduate students. Procedure calls, stacks, interrupts, and traps. Lecture, four hours; discussion, two hours; outside study, six hours. May be repeated for credit. Letter grading. S/U grading. Designed for undergraduate students who are part of research group. Development and application of computational approaches to biological questions, with focus on formulating interdisciplinary problems as computational problems and then solving these problems using algorithmic techniques. Tutorial, to be arranged. Review of current literature in area of data structures in which instructor has developed special proficiency as consequence of research interests.

Letter grading. Lecture, four hours; outside study, eight hours. Tutorial, to be arranged. Topics include genome analysis, regulatory genomics, association analysis, association study design, isolated and admixed populations, population substructure, human structural variation, model organisms, and genomic technologies. Techniques and examples used in areas such as healthcare, financial systems, commerce, and social networking.

Number systems, machine language, and assembly language. Lecture, four hours; outside study, eight hours. May be repeated for credit with topic change. Emphasis on applications in simulation of physical systems. Seminar, two hours; outside study, four hours. S/U or 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. Elliptic curve methods. Letter grading. May be repeated for credit. Teaches students how to use computers as tool for problem solving, creativity, and exploration through design and implementation of computer programs. (Same as Electrical and Computer Engineering M202A.) Computer Science Majors Only. Numerical simulation, optimization, and parameter identifiability and search algorithms, with model discrimination and analysis and software exercises in PC laboratory assignments. Principles for efficient implementation. Lecture, four hours; outside study, eight hours. Tutorial, to be arranged. Focus on sequence analysis and alignment algorithms. Students must be in good academic standing and enrolled in minimum of 12 units (excluding this course). Tutorial, to be arranged. Current CS Science and Technology (Sci-Tech) Options. Searching and sorting. Dynamic biosystem modeling and computer simulation methods for studying analyzing biological/biomedical processes and systems at multiple levels of organization. Lecture, four hours; outside study, eight hours.

Letter grading. Precursor course to introductory computer science sequence (courses 31, 32, 33).

(Same as Bioengineering M296D.) Each member completes one tutorial and one or more original pieces of work in one specialized area. Topics include Markov chain Monte Carlo computing, sequential Monte Carlo methods, belief propagation, partial differential equations. (Same as Mathematics M209B.) Concurrently scheduled with course CM186. Introduction to explicit modeling and simulation of dynamic biological systems. P/NP grading. Enforced requisite: course 188SA. Seminar, four hours; outside study, eight hours. Types of algorithms and implementations. (Same as Bioinformatics M225 and Human Genetics M265.)

Computer software systems performance, robustness, and functionality. Logic and algorithmization of counterfactuals. Letter grading. Letter grading. Examination of statistical and computational aspects of machine learning techniques and their application to key biological questions. Lecture, four hours; outside study, eight hours. Letter grading. Additional requisites for each offering announced in advance by department. Basic number theory, including congruences and prime numbers. Intermediate queueing theory: M/G/1, G/M/m. LSI/VLSI design and application in computer systems. Letter grading.

Requisite: course 111. (Formerly numbered M117.) Bottleneck in being able to make sense of biological processes has shifted from data generation to statistical models and inference algorithms that can analyze these datasets. Supervised independent research for MS candidates, including thesis prospectus. Integrity and authorization. Seminar, two hours; outside study, four hours.

Enforced requisite: course 118. Letter grading. Review of current literature in area of computer science system design in which instructor has developed special proficiency as consequence of research interests. Examination of both symbolic and statistical approaches to language processing and acquisition. Letter grading. Important concepts and theory for building effective and safe Web applications and first-hand experience with basic tools. Collective marks. Letter grading. Enforced requisites: courses 33, 35L. Letter grading. Discussion of advanced topics and current research in algorithmic processes that describe and transform information: theory, analysis, design, efficiency, implementation, and application. Introduction to basic concepts of information security necessary for students to understand risks and mitigations associated with protection of systems and data. Designed for students undertaking thesis research.

In-depth treatment of systematic problem-solving search algorithms in artificial intelligence, including problem spaces, brute-force search, heuristic search, linear-space algorithms, real-time search, heuristic evaluation functions, two-player games, and constraint-satisfaction problems. Letter grading. Searching and accessing databases and across Internet by alphanumeric, image, video, and audio content. Lecture, four hours; outside study, eight hours. Designed for junior/senior Computer Science majors. Topics from coding theory: Hamming codes, cyclic codes, Gilbert/Varshamov bounds, Shannon theorem. Recommended: course 251A. Overloading, inheritance, polymorphism. Other topics at discretion of instructor. May be repeated for credit with consent of instructor and topic change. Lecture, four hours; outside study, eight hours. Cryptography: public-key and discrete log cryptosystems.


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