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Courses in Electrical Engineering and Computer Science
This page was created at 5:38 PM on Thu, Oct 3, 2002.
Fall Academic Term, 2002 (September 3  December 20)
EECS 427. VLSI (Very Large Scale Integrated) Design I.
Computer Science
Instructor(s):
Prerequisites: EECS 270 and 311. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Design techniques for rapid implementations of very large scale integrated (VLSI) circuits, MOS technology and logic. Structured design. Design rules, layout procedures. Design aids: layout, design rule checking, and logic and circuit simulation. Timing. Testability. Architectures for VLSI. Projects to develop and lay out circuits.
EECS 470. Computer Architecture.
Computer Science
Instructor(s):
Prerequisites: EECS 370. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/courses/eecs470/
Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queueing models. CPU architecture. Instruction sets. ALU design. Hardwired and microprogrammed control. Nanoprogramming. Memory hierarchies. Virtual memory. Cache design. Inputoutput architectures. Interrupts and DMA. I/O processors. Parallel processing. Pipelined processors. Multiprocessors.
EECS 477. Introduction to Algorithms.
Computer Science
Instructor(s):
Prerequisites: EECS 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Fundamental techniques for designing efficient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divideandconquer, greedy methods, graph search techniques, and dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.
EECS 478. Logic Circuit Synthesis and Optimization.
Computer Science
Instructor(s):
Prerequisites: EECS 270 and 203, and senior or graduate standing. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Advanced design of logic circuits. Technology constraints. Theoretical foundations. Computeraided design algorithms. Twolevel and multilevel optimization of combinational circuits. Optimization of finitestate machines. Highlevel synthesis techniques: modeling, scheduling, and binding. Verification and testing.
EECS 481. Software Engineering.
Computer Science
Instructor(s):
Prerequisites: EECS 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Pragmatic aspects of the production of software systems, dealing with structuring principles, design methodologies, and informal analysis. Emphasis is given to development of large, complex software systems. A term project is usually required.
EECS 482. Introduction to Operating Systems.
Computer Science
Instructor(s):
Prerequisites: EECS 370 and 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~pmchen/eecs482/
Operating system design and implementation: multitasking; concurrency and synchronization; interprocess communication; deadlock; scheduling; resource allocation; memory and storage management; inputoutput; file systems; and protection and security. Students write several substantial programs dealing with concurrency and synchronization in a multitask environment, with file systems, and with memory management.
EECS 482. Introduction to Operating Systems.
Computer Science
Instructor(s):
Prerequisites: EECS 370 and 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~pmchen/eecs482/
No Description Provided. Contact the Department.
EECS 483. Compiler Construction.
Computer Science
Instructor(s):
Prerequisites: EECS 281 or graduate standing. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://wwwpersonal.engin.umich.edu/~jcaputo/eecs483/
Introduction to compiling techniques including parsing algorithms, semantic processing, and optimization. Students implement a compiler for a substantial programming language using a compiler generating system.
The class will have about 6 homeworks and no exams. The grades will be 40% homeworks and 60% projects.
Books:
 Lex & Yacc (Required) by Levine, Mason, Brown O'Reilly Publishers
 Compilers: Principles, Techniques, and Tools (Required) Alfred V. Aho, Ravi Sethi, Jeffrey Ulman
 Mastering Regular Expression (Recommendd) Powerful Techniques for Perl and Other Tools By Jeffrey Friedl O'Reilly
Publishers
EECS 484. Database Management Systems.
Computer Science
Instructor(s):
Prerequisites: EECS 380. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/courses/eecs484/
EECS 484 provides basic introduction to relational database management systems (DBMSs). This course
is designed to provide you with both an external and an internal view of relational DBMSs. Topics related
to the external view will cover concepts that will allow you to use a relational DBMS. Topics related to the
internal view will allow you to better understand how a relational DBMS works, making you more
sophisticated (and perhaps higher paid) database users/administrators. The course has a group course
project in which you will build a simple, but fairly complete, singleuser relational database engine. Note,
in this course you will not learn the details of how to use any specific commercial database system, or the
intricacies of SQL programming. This course is designed to cover the fundamental database concepts and
the implementation techniques that are used in relational database engines. Using the course project,
you will actually build a few key components of a database engine. If you are interested in the details of
SQL programming, or the operation of a specific commercial database system, you will be able to pick
this up very easily after you have taken this course.
EECS 487. Interactive Computer Graphics.
Computer Science
Instructor(s):
Prerequisites: EECS 281 and senior standing. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Computer graphics hardware, line drawing, rasterization, antialiasing, graphical user interface (GUI), affine geometry, projective geometry, geometric transformation, polygons, curves, splines, solid models, lighting and shading, image rendering, ray tracing, radiosity, hidden surface removal, texture mapping, animation, virtual reality, and scientific visiualization.
EECS 489. Computer Networks.
Computer Science
Instructor(s):
Prerequisites: EECS 482. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://devon.eecs.umich.edu/
Textbooks:
 Kurose and Ross, "Computer Networking: A TopDown Approach," 2nd. ed., AddisonWesley, 2002. ISBN 020147114.
 W.R. Stevens, UNIX Network Programming, vol. 1: Networking APIs: Sockets and XTI, 2nd. ed., PrenticeHall, 1997. (Don't buy the first edition!).
If you want to learn how to design waycool Web pages, how to build and maintain a killer Web site, or how to setup, administer, and engineer a LAN, this course is not for you. In this course we do not study how modem works, nor
do we study how ISDN works. We do not study Novell Netware Administration and we do not learn how to use Adobe
Photoshop. We do not learn how to set up a chat room, nor how to set up an electronic guest book.
We do try to understand how networks operate and how network applications are written. We study the workings of
the Ethernet and the Internet: how packets are routed, how packets are transmitted, and what to do when there is
network congestion. We look at packet headers and routing and transmission protocols. We learn what sockets are
and how to use them. And we write code. We write code to implement various routing and transmission protocols.
We write code to build clientserver applications. There will be a lot of programming. You should know what processes and threads are and be familiar with concurrency and interprocess
communication. EECS 482 (Introduction to Operating Systems) is a strict prerequisite. You must also have good
working knowledge of C and UNIX. An introduction to probability course such as EECS 401, EECS 501, Math 425, Math 525, or Stat 412 is highly recommended as a corequisite.
EECS 492. Introduction to Artificial Intelligence.
Computer Science
Instructor(s):
Prerequisites: EECS 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: https://coursetools.ummu.umich.edu/2002/fall/eecs/492/001.nsf
The purpose of this course is to introduce the student to the major
ideas and techniques of Artificial Intelligence, as well as to develop an
appreciation for the engineering issues underlying the design of
intelligent, computational agents. The successful student will finish the
course with specific modeling and analytical skills (e.g., search, logic, probability), knowledge of many of the most important knowledge
representation, reasoning, and machinelearning schemes, and a
general understanding of AI principles and practice. The course will
serve to prepare the student for further study of AI, as well as to
inform any work involving the design of computer programs for
substantial application domains.
EECS 494. Computer Game Design and Development.
Computer Science
Instructor(s):
Prerequisites: EECS 281. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Concepts and methods for the design and development of computer games. Topics include: history of games, 2D graphics and animation, sprites, 3D animation, binary space partition trees, software engineering, game design, interactive fiction, user interfaces, artificial intelligence, game SDK's, networking, multiplayer games, game development environments, and commercialization of software.
EECS 497. EECS Major Design Projects.
Computer Science
Instructor(s):
Prerequisites: Senior standing. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Professional problemsolving methods developed through intensive group studies. Normally, one significant design project is chosen for entire class requiring multiple EECS disciplines and teams. Use of analytic, computer, design, and experimental techniques where applicable are used. Projects are often interdisciplinary allowing nonEECS seniors to also take the course (consult with instructor).
EECS 498. Special Topics.
Computer Science
Instructor(s):
Prerequisites: (14). CAEN lab access fee required for nonEngineering students.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Topic of current interest selected by faculty.
EECS 498. Special Topics.
Computer Science
Section 001 – Programming Science and Engineering
Instructor(s):
A Morgan
Prerequisites: (14). CAEN lab access fee required for nonEngineering students.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
EECS 498. Special Topics.
Computer Science
Section 003 – Patent Fundamentals for Engineers. (3 credits).
Instructor(s):
M Islam
Prerequisites: (14). CAEN lab access fee required for nonEngineering students.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
EECS 570. Parallel Computer Architecture.
Computer Science
Instructor(s):
Prerequisites: EECS 470. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/courses/eecs570/
Pipelining and operation overlapping, SIMD and MIMD architectures, numeric and nonnumeric applications, VLSI, WSI architectures for parallel computing, and performance evaluation. Case studies and term projects.
EECS 574. Theoretical Computer Science.
Computer Science
Computational Complexity Theory
Instructor(s):
Satyanarayana V. Lokam
Prerequisites: EECS 376. (4). CAEN lab access fee required for nonEngineering students.
Credits: (4).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~satyalv/tcs/
We will cover the following basic topics:
 Turing Machine Model of Computation
 Recursively Enumerable and Recursive Languages, Undecidability
 Time and Space Complexity Classes, Hierarchy Theorems
 Relations between DTIME, NTIME, DSPACE, NSPACE
 Savitch's Theorem, ImmermanSzelepcsenyi Theorem
 Standard Complexity Classes: L, NL, P, NP, PSPACE, EXP
 Reductions and Completeness, polytime and logspace reductions
 CookLevin: NPCompleteness of SAT, Examples of NPComplete Problems
 NLCompleteness of Reachability
 PCompleteness of Circuit Value Problem, Examples of PComplete Problems
 P vs NP, NP vs CoNP, L vs NL vs P
 Oracle Computations, Alternating Turing Machines, PH, PSPACE
 PSPACECompleteness of TQBF, Examples of PSPACEComplete Problems
 Function Classes, #P,
 Valiant: #Pcompleteness of PERMANENT, Examples of #PComplete Functions
 Randomized Complexity Classes: BPP, ZPP, RP
 P vs BPP
In addition, we will try to survey the following advanced areas:
 Randomness + Nondeterminism
 Interactive Proof Systems, ArthurMerlin Games
 IP = PSPACE
 Probabilistically Checkable Proof Systems
 Overview of NP = PCP(log n, 1)
 Inapproximability of some NPcomplete problems
 Nonuniform Complexity
 Boolean Circuits
 Lower Bounds on Monotone Circuits
 Decision Trees and Branching Programs, Barrington's Theorem
 Communication Complexity
EECS 579. Digital System Testing.
Computer Science
Section 001.
Prerequisites: Graduate standing. (3). CAEN lab access fee required for nonEngineering students.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~mazum/F02/
Introduction to faulttolerant computing and digital testing. Fault classification, char
acterization of physical defects, fault modeling, hierarchy of fault models, and testing terminolo
gies. Test generation algorithms. Combinational circuit testing: Dalgorithm, PODEM, FAN, etc.
for stuckat faults; Bridging faults testing; Delay faults testing. Functional testing of arithmetic
and regular arrays. Synchronous and asynchronous sequential circuit testing. Memory (RAM,
ROM and CAM), register file, and FIFO buffer testing. IDDQ testing and current monitoring.
Functional testing of microprocessors and microcontrollers. Design for testability.Testability
measures. Boundary scan and partial scan design. Test data and response compression. Builtin
selftesting. Selftesting of RAMs, ROMs and PLAs. Pseudorandom testing. Estimation of test
coverage by random test vectors: memories and logic blocks. Systemonchip (SOC) testing. In
tellectual Property (IP) and embedded core testing. Modern issues in digital testing.
The objective of this course is to understand the failure mechanisms in VLSI chips and character
ization of failures at various levels of circuit hierarchy and finally to develop appropriate testing
strategies. Test generation algorithms are segregated into different classes based on the circuits
they are intended to test: combinational circuit testing, synchronous and asynchronous sequential
logic testing in the presence of flipflops, and testing of large storage arrays such as RAM's,
ROM's and FIFO's. Further,how much one needs to test also depends on the composition of cir
cuit blocks: a simple logical fault describing a signal line is shorted to ground or to power supply
can suffice for random and glue logic scattered all over a chip, while for extremely finegrained
array of memory cells, occupying a large chunk of chip real estate, may require more complex
fault model that will account for anomalies in masking, process parameters and chip layout.
Text Book:
M. Bushnell, and V. D. Agarwal, Essential of Electronic Testing for Digital, Memory and Mixed Signal VLSI Circuits,
Kluwer Aacdemic Press,, Boston, 2000, 690 pages
Supplementary Text Book:
 P. Mazumder and K.Chakraborty, Testing and Testable Design of RandomAccess Memories,
Kluwer Academic Publishers, New York, 1996, 430 pages.
 M. Abramovici, M. A. Breuer, and A. D. Friedman, Digital System Testing and Testable Design,
IEEE Press, New York, 1990, 652 pages (an early version of the same book was published by Computer Science Press).
Evaluation:
Homework Assignments(6): 30%; Project: 30%;
Midterm(2): 20%; Final Exam: 20%.
EECS 584. Advanced Database Systems.
Computer Science
Instructor(s):
Prerequisites: EECS 484. (3). CAEN lab access fee required for nonEngineering students.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Survey of advanced topics in database systems. Distributed databases, query processing, and transaction processing. Effects of data models: objectoriented and deductive databases, architectures, mainmemory and parallel repositories, distributed organizations, and clientserver and heterogeneous systems. Basic data management for emerging areas: Internet applications, OLAP, and data mining. Case studies of existing systems. Group projects.
EECS 587. Parallel Computing.
Computer Science
Section 001.
Prerequisites: EECS 281 and graduate standing. (3). CAEN lab access fee required for nonEngineering students.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~qstout/587/index.html
Audience: Typically about half the class is from Computer Science and Engineering, and half is from a wide range of other areas throughout the
sciences, engineering, and medicine. Some students want to become parallel computing specialists, while others intend to apply parallel
computing to their discipline. Students range from seniors through postdocs, and occasionally faculty sit in on the course as well.
Content: The course covers a wide range of aspects of parallel computing, with the emphasis on developing efficient software for commercially
available systems. Because there is not a single parallel computing model, you also have to learn some about various parallel
architectures, since there is significant hardware/software interaction. This includes aspects such as shared vs. distributed memory,
clustering, cache coherency, interconnection networks, finegrain vs. mediumgrain, and MIMD/SIMD. For fun, we may briefly discuss some
more exotic parallel models, such as DNA computing, quantum computing, or processorinmemory systems. Various operating system and
language issues are also covered. In particular, we will emphasize using standard software, especially MPI (Message Passing Interface) and
OpenMP. Use of standard software helps make the code more portable, preserving the time invested in it.
We examine many reasons for poor parallel performance, and a wide range of techniques for improving it. Concepts such as domain
decomposition; deterministic, probabilistic and adaptive load balancing; and sychronization will be covered. You'll learn why modest
parallelization is relatively easy to achieve, and why efficient massive parallelization is quit difficult  in particular, we will cover various
implications of Amdahl's Law. Examples and programs will be numeric, such as matrix multiplication, and nonnumeric, such as sorting. v
Here is a somewhat whimsical overview of what parallel computing is.
Work required: Your grade will be based on written homeworks, computer programming projects, and a final project of your choosing (though I must
approve it). Often students can integrate this project in with their other work, so, for example, it may be part of their thesis. Many other
students have used this project to start a new research area, and have ultimately gotten a thesis in the topic. Many of the projects have
lead to publications, and a few have resulted in awards of various types. If you don't have any ideas for a project, I'll help you find some.
Here is some more information and suggestions for the final project.
Prerequisites: Ability to program well in C or Fortran, plus an ability to analyze programs, plus willingness to rethink how problems should be solved. You
do not need any prior experience with parallel computing or supercomputing, nor do you need to have a background in numerical analysis.
However, you do need to be a good programmer  after all, it makes little sense to use an expensive supercomputer if you can't utilize a
regular computer well.
Computing Resources: The class will use the parallel machines in the Center for Parallel Computing (CPC) here at the University of Michigan. These include an IBM
SP2, an SGI PowerChallenge, an SGI Origin, and a PCbased cluster computer. Sometimes, for illustrative purposes, the class itself will be
the parallel computer.
Texts: None, but you will need to buy some computer manuals and you will have lots of papers and web resources to read. (You could always buy
the professor's book, but it is not really relevant to the course.)
EECS 595 / LING 541. Natural Language Processing.
Computer Science
Section 001.
Prerequisites: Senior standing. (3). CAEN lab access fee required for nonEngineering students.
Credits: (3).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~rthomaso/cl/clcourse.html
See Linguistics 541.001.
EECS 597 / LING 702 / SI 760. Language and Information.
Section 001.
Prerequisites: (3).
Credits: (3).
Course Homepage: http://perun.si.umich.edu/~radev/760/syllabus.html
See Linguistics 702.001.
EECS 598. Special Topics in Electrical Engineering and Computer Science.
Computer Science
Instructor(s):
Prerequisites: Permission of instructor or advisor. (14). CAEN lab access fee required for nonEngineering students. May be repeated for credit.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory.
EECS 598. Special Topics in Electrical Engineering and Computer Science.
Computer Science
Section 001 – RF Power Amplifier Design. [credits?].
Instructor(s):
A Mortazawi
Prerequisites: Permission of instructor or advisor. (14). CAEN lab access fee required for nonEngineering students. May be repeated for credit.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
EECS 598. Special Topics in Electrical Engineering and Computer Science.
Computer Science
Section 002 – Analog to Digital Conversion Circuits. [credits?].
Instructor(s):
M Flynn
Prerequisites: Permission of instructor or advisor. (14). CAEN lab access fee required for nonEngineering students. May be repeated for credit.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
EECS 598. Special Topics in Electrical Engineering and Computer Science.
Computer Science
Section 003 – Theory of Quantum Computation: Introduction and Current Problems. [credits?].
Prerequisites: Permission of instructor or advisor. (14). CAEN lab access fee required for nonEngineering students. May be repeated for credit.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: http://www.eecs.umich.edu/~shiyy/598/
As a result of remarkable theoretical advances in recent years, the emerging field of quantum computation has drawn enthusiastic participations from scientists in many fields. It has been demonstrated that quantum information behaves fundamentally differently from classical information, and, it appears that computers based on exact quantum mechanical principles can be dramatically more powerful than those currently deployed.
This course is to provide an introduction to the theory of quantum computation, as well as to explore its frontier. Topics include, but are not limited to:
 Mathematical foundations of quantum mechanics and models of quantum computation;
 Quantum algorithms;
 Classical simulations of quantum circuits;
 Quantum lower bounds;
 Quantum communication complexity;
 Quantum errorcorrecting codes, and faulttolerant quantum computation;
 Quantum cryptography.
The course is intended for all interested and mathematically mature audiences. Collegelevel linear algebra is required. Knowledge in quantum
mechanics and theoretical computer science is helpful, but not required.
Reference Books
 A. Yu. Kitaev, A. H. Shen and M. N. Vyalyi. Classical and Quantum Computation, American Mathematical Society, July 2002. ISBN: 0821832298.
 John Preskill. Quantum Information and Computation, Lecture notes available at http://theory.caltech.edu/people/preskill/ph229/.
 Isaac L. Chuang and M. A. Nielsen. Quantum Computation and Information, Cambridge University Press, December 2000. ISBN: 0521635039.
EECS 598. Special Topics in Electrical Engineering and Computer Science.
Computer Science
Section 004.
Instructor(s):
Wise
Prerequisites: Permission of instructor or advisor. (14). CAEN lab access fee required for nonEngineering students. May be repeated for credit.
Credits: (14).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
No Description Provided. Contact the Department.
EECS 990. Dissertation/Precandidate.
Computer Science
Instructor(s):
Prerequisites: Election for dissertation work by doctoral student not yet admitted as a Candidate.Graduate standing. (18). CAEN lab access fee required for nonEngineering students. (INDEPENDENT). May be repeated for credit.
Credits: (18; 14 in the halfterm).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Election for dissertation work by doctoral student not yet admitted as a Candidate.
EECS 995. Dissertation/Candidate.
Computer Science
Instructor(s):
Prerequisites: Graduate School authorization for admission as a doctoral Candidate. (8). CAEN lab access fee required for nonEngineering students. (INDEPENDENT). May be repeated for credit.
Credits: (8; 4 in the halfterm).
Lab Fee: CAEN lab access fee required for nonEngineering students.
Course Homepage: No homepage submitted.
Graduate School authorization for admission as a doctoral Candidate. N.B. The defense of the dissertation (the final oral examination) must be held under a full term Candidacy enrollment period.
This page was created at 5:38 PM on Thu, Oct 3, 2002.
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