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Course Criteria
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3.00 Credits
OPEN ONLY TO STUDENTS MAJORING IN FINANCE. FUND DATA STRUCT AND THEIR IMPLEMENTATIONS:STACKS QUEUES,TREES,HEAPS GRAPHS,HASH TABLES.SEARCHING AND SORTING ALGORITHMS, ETC.
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3.00 Credits
Principles of artificial intelligence. Topics include logic and deduction; resolution theorem proving; space search and game playing; language parsing; image understanding; machine learning and expert systems. Programming projects in LISP, PROLOG, or related languages.
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3.00 Credits
Principles and implementation of programming languages. Topics include: the procedure, object-oriented, functional, and logic programming paradigms, syntax (BNF, expression grammars, operator precedence and associativity), variables (scope, storage bindings, and lifetime), data types, control structures, function call and return (activation records and parameter passing), formal semantics. Programming assignments.
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3.00 Credits
Formal definitions of programming languages: introduction to compiler construction including lexical, syntactic, and semantic analysis, code generation, and optimization.
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3.00 Credits
Introduction to the hardware and software components of graphics systems, fundamental algorithms for the generation of two-dimensional display (lines, fill areas, curves, characters), transformation and viewing algorithms, methods of organizing picture components into segments, interactive input, Graphical Kernel System (GKS) routine calls, color models, introduction to three-dimensional techniques. Programming projects to demonstrate the implementation of graphic algorithms.
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3.00 Credits
Finite state machines, regular languages, regular expressions, grammars, context-free languages, pushdown automata, Turing machines, recursive sets, recursively enumerable sets, reductions, Halting problem, diagonalization.
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3.00 Credits
No course description available.
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3.00 Credits
No course description available.
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3.00 Credits
Advanced data structures: B-trees, graphs, hash-tables. Problem-solving strategies including divide-and-conquer, backtracking, dynamic programming, and greedy algorithms. Advanced graph algorithms. Time complexity analysis. NP-complete problems. Applications to sorting, searching, strings, graphs. Programming projects.
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3.00 Credits
No course description available.
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