CSE 410 Computer Systems (3)
Structure and components of hardware and software systems. Machine organization, including central processor and input-output architectures; assembly language programming; operating systems, including process, storage, and file management. Intended for non-majors. No credit to students who have completed CSE 351, CSE 378, or CSE 451. Prerequisite: CSE 373.
CSE 417 Algorithms and Computational Complexity (3)
Design and analysis of algorithms and data structures. Efficient algorithms for manipulating graphs and strings. Fast Fourier Transform. Models of computation, including Turing machines. Time and space complexity. NP-complete problems and undecidable problems. Intended for non-majors. Prerequisite: CSE 373.
CSE 446 Machine Learning (3)
Methods for designing systems that learn from data and improve with experience. Supervised learning and predictive modeling: decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. Unsupervised learning and clustering. Prerequisite: either CSE 326 or CSE 332; either STAT 390, STAT 391, or CSE 312.
CSE 415 Introduction to Artificial Intelligence (3) NW
Principles and programming techniques of artificial intelligence: LISP, symbol manipulation, knowledge representation, logical and probabilistic reasoning, learning, language understanding, vision, expert systems, and social issues. Intended for non-majors. Not open for credit to students who have completed CSE 473. Prerequisite: CSE 373.
CSE 373 Data Structures and Algorithms (3)
Fundamental algorithms and data structures for implementation. Techniques for solving problems by programming. Linked lists, stacks, queues, directed graphs. Trees: representations, traversals. Searching (hashing, binary search trees, multiway trees). Garbage collection, memory management. Internal and external sorting