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CS 433: Computer System Organization
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Computer system analysis and design. Organizational dependence on computations to be performed. Speed and cost of parts and overall machines. Instruction set design. Pipeline and vector machines. Memory hierarchy design. Same as CSE 422. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 232.
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CS 433 - Computer System Organization
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CS 435: Intro to VLSI System Design
3.00 Credits
University of Illinois at Urbana-Champaign
Same as CSE 433 and ECE 425. See ECE 425.
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CS 435 - Intro to VLSI System Design
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CS 436: Computer Networking Laboratory
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Same as ECE 435. See ECE 435.
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CS 436 - Computer Networking Laboratory
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CS 438: Communication Networks
3.00 Credits
University of Illinois at Urbana-Champaign
Layered architectures and the OSI Reference Model; design issues and protocols in the transport, network, and data link layers; architectures and control algorithms of local-area, point-to-point, and satellite networks; standards in networks access protocols; models of network interconnection; overview of networking and communication software. Same as CSE 425 and ECE 438. Prerequisite: CS 241 or ECE 391; one of MATH 461, MATH 463, ECE 313.
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CS 438 - Communication Networks
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CS 439: Wireless Networks
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Same as ECE 439. See ECE 439.
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CS 439 - Wireless Networks
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CS 440: Artificial Intelligence
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Major topics in and directions of research in artificial intelligence: AI languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. Same as ECE 448. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225 or ECE 391.
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CS 440 - Artificial Intelligence
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CS 443: Introduction to Robotics
4.00 Credits
University of Illinois at Urbana-Champaign
Same as AE 482, ECE 470, GE 421, and ME 445. See ECE 470.
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CS 443 - Introduction to Robotics
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CS 446: Machine Learning
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Theory and basic techniques in machine learning. Major theoretical paradigms and key concepts developed in machine learning in the context of applications such as natural language and text processing, computer vision, data mining, adaptive computer systems and others. Review of several supervised and unsupervised learning approaches: methods for learning linear representations; on-line learning, Bayesian methods; decision-trees; features and kernels; clustering and dimensionality reduction. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 373 and CS 440.
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CS 446 - Machine Learning
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CS 450: Numerical Analysis
3.00 - 4.00 Credits
University of Illinois at Urbana-Champaign
Introduction to numerical analysis, including linear system solvers, optimization techniques, interpolation and approximation of functions, solving systems of nonlinear equations, eigenvalue problems, least squares, and quadrature; numerical handling of ordinary and partial differential equations. Same as CSE 401, ECE 491, and MATH 450. 3 undergraduate hours. 3 or 4 graduate hours. Credit is not given for both CS 450 and CS 457. Prerequisite: CS 101 or CS 125; CS 357 or MATH 415; MATH 285.
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CS 450 - Numerical Analysis
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CS 457: Numerical Methods II
3.00 Credits
University of Illinois at Urbana-Champaign
Continuation of CS 357. Orthogonalization methods for least squares, Krylov subspace methods, non-linear equations and optimization in multiple dimensions, initial and boundary value problems for ordinary and partial differential equations. No graduate credit. Credit is not given for both CS 457 and CS 450. Prerequisite: CS 357.
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CS 457 - Numerical Methods II
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