CS 294A: Research Project in Artificial Intelligence
Student teams under faculty supervision work on research and implementation of a large project in AI. State-of-the-art methods related to the problem domain. Prerequisites: AI course from 220 series, and consent of instructor.
Last offered: Winter 2012
| Repeatable
for credit
CS 294S: Research Project in Software Systems and Security
Topics vary. Focus is on emerging research themes such as programmable open mobile Internet that spans multiple system topics such as human-computer interaction, programming systems, operating systems, networking, and security. May be repeated for credit. Prerequisites:
CS 103 and 107.
Terms: Spr
| Units: 3
| Repeatable
for credit
Instructors:
Lam, M. (PI)
CS 294W: Writing Intensive Research Project in Computer Science
Restricted to Computer Science and Computer Systems Engineering undergraduates. Students enroll in the
CS 294W section attached to the
CS 294 project they have chosen.
Terms: Spr
| Units: 3
Instructors:
Lam, M. (PI)
CS 295: Software Engineering
Software specification, testing, and verification. Emphasis is on current best practices and technology for developing reliable software at reasonable cost. Assignments focus on applying these techniques to realistic software systems. Prerequisites: 108. Recommended a project course such as 140, 143, or 145.
Last offered: Spring 2011
CS 298: Seminar on Teaching Introductory Computer Science (EDUC 298)
Faculty, undergraduates, and graduate students interested in teaching discuss topics raised by teaching computer science at the introductory level. Prerequisite: consent of instructor.
Terms: Aut
| Units: 1
Instructors:
Cooper, S. (PI)
;
Grover, S. (PI)
CS 300: Departmental Lecture Series
Priority given to first-year Computer Science Ph.D. students. CS Masters students admitted if space is available. Presentations by members of the department faculty, each describing informally his or her current research interests and views of computer science as a whole.
Terms: Aut
| Units: 1
Instructors:
Dill, D. (PI)
CS 309A: Cloud Computing
For science, engineering, business, medicine, and law students. Cloud computing is bringing information systems out of the back office and making it core to the entire economy. This class is intended for all students who want to begin to understand the implications of this shift in technology. Guest industry experts are public company CEOs who are delivering application, software development, operations management, compute, storage & data center, and network cloud services.
Terms: Aut
| Units: 1
| Repeatable
for credit
Instructors:
Chou, T. (PI)
CS 316: Advanced Multi-Core Systems (EE 382E)
In-depth coverage of the architectural techniques used in modern, multi-core chips for mobile and server systems. Advanced processor design techniques (superscalar cores, VLIW cores, multi-threaded cores, energy-efficient cores), cache coherence, memory consistency, vector processors, graphics processors, heterogeneous processors, and hardware support for security and parallel programming. Students will become familiar with complex trade-offs between performance-power-complexity and hardware-software interactions. A central part of CS316 is a project on an open research question on multi-core technologies. Prerequisites:
EE 108B. Recommended:
CS 149,
EE 282.
Terms: Aut
| Units: 3
Instructors:
Kozyrakis, C. (PI)
CS 319: Topics in Digital Systems
Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. May be repeated for credit.
| Repeatable
for credit
CS 323: Automated Reasoning: Theory and Applications
Intelligent computer agents must reason about complex, uncertain, and dynamic environments. This course is a graduate level introduction to automated reasoning techniques and their applications, covering logical and probabilistic approaches. Topics include: logical and probabilistic foundations, backtracking strategies and algorithms behind modern SAT solvers, stochastic local search and Markov Chain Monte Carlo algorithms, variational techniques, classes of reasoning tasks and reductions, and applications.
Terms: Spr
| Units: 3-4
Instructors:
Ermon, S. (PI)
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