CSE 4153 Introduction to Artificial Intelligence (CSE 373 prereq)

Congratulations Marty!!!! As Ed said you have contributed much here and not just in CSE. Many of our iSchool Informatics students have told me your CSE 154/190M course was among the best classes they’ve taken. You’ve also worked hard with other departments to improve non-major classes like CSE 373, and our students have noticed and really appreciated your efforts. We wish you all the very best at Stanford!!!!

Our required textbook for CSE 373 this quarter is either edition:

CSE 373: Design and Analysis of Algorithms

CSE 373: Data Structures and Algorithms

Introduction; Point operations; Histograms; Spatial operations; Affine transformations; Image rectification; Interpolation and other transformations; Contrast enhancement; Convolution operation, Magnification and Zooming; Fourier transform; Edge detection; Boundary extraction and representation; Mathematical morphology. Prerequisite: CSE 373. 3 credits.

UW CSE373, Fall 2015 - University of Washington

Introduction: Basic concepts, Design concepts, Examples; Decision functions: Linear decision functions, Generalized decision functions; Pattern classification by distance functions: Minimum distance pattern classification, Cluster seeking; Pattern classification by likelihood functions: Bayes classifier; Structural pattern representation: Grammars for pattern representation, Picture description language and grammars, Stochastic grammars; Structural pattern recognition: String to string distance; Matching other structures: Relational structures, Graph matching, Matching by relaxation, Random graph. Prerequisite: CSE 373. 3 credits.

CSE 373-8
Besides the fact that CSE 373 is only 3 credits and has no quiz section, the only major difference the fact that CSE 332 dedicates 3 weeks to dealing with parallelism and concurrency whereas CSE 373 spends more time on abstract data types. Most notably, CSE 373 goes more in-depth on the implementation of the disjoint set data structure and has more time for review of basic data structures (ex BST) whereas CSE 332 moves at a slightly faster pace to be able to make sure there's time at the end of the quarter to cover concurrency and parallelism.Mathematical analysis of a variety of computer algorithms including searching, sorting, matrix multiplication, fast Fourier transform, and graph algorithms. Time and space complexity. Upper-bound, lower- bound, and average-case analysis. Introduction to NP completeness. Some machine computation is required for the implementation and comparison of algorithms. This course is offered as CSE 373 and MAT 373.Acknowledgments: Many of the materials posted here and used in thecourse have been shared and refined by many other instructors and TAs in previous offerings ofCSE373, CSE332, and CSE326. This version of the course wasparticularly based on previous offerings by Ruth Anderson and Dan Grossman.Acknowledgments: Many of the materials posted here and used in thecourse have been shared and refined by many other instructors and TAs in previous offerings ofCSE373, CSE332, and CSE326. This version of the course wasparticularly based on previous offerings by Ruth Anderson.
CSE 3734

This course is offered as CSE 373 and MAT 373.

Acknowledgments: Many of the materials posted here and used in thecourse have been shared and refined by many other instructors and TAs in previous offerings ofCSE373, CSE332, and CSE326. This version of the course wasparticularly based on previous offerings by Ruth Anderson.

CSE 3738

Test Bank: CSE 373: Washington (UW): Koofers

Finite automata and regular languages, pushdown automata and context-free languages; Turing machines and recursively enumerable sets; linear-bounded automata and context sensitive languages; computability and the halting problem; undecidable problems; recursive functions; chomsky hierarchy; computational complexity. Prerequisite: CSE 373 and MAT 361 or consent of instructor. 3 credits.

Model: CSE 373-8

CSE 373 Data Structures and Algorithms

Mathematical analysis of a variety of computer algorithms including searching, sorting, matrix multiplication, fast Fourier transform, and graph algorithms. Time and space complexity. Upper-bound, lower- bound, and average-case analysis. Introduction to NP completeness. Some machine computation is required for the implementation and comparison of algorithms. This course is offered as CSE 373 and MAT 373.