The Course explores key concepts of artificial intelligence, including state-space and heuristic search techniques, game playing, knowledge representation, automated planning, reasoning under uncertainty, decision theory and machine learning. We will examine how these concepts are applied in the context of several applications.

The design and operation of modern computer operating systems. Review of capabilities of typical computer hardware. Topics include command language interpreter (the shell), processes, concurrency, inter-process communication, linking and loading, memory management, transactions, file systems, distributed systems, security, and protection. Programming projects in Java and C.

The design and operation of modern computer operating systems. Review of capabilities of typical computer hardware. Topics include command language interpreter (the shell), processes, concurrency, inter-process communication, linking and loading, memory management, transactions, file systems, distributed systems, security, and protection. Programming projects in Java and C.

In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stages of the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, communication, teamwork, and software project management. Particular emphasis is placed on communication and negotiation skills and on designing and developing maintainable software.

The design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures and on measures of algorithmic efficiency. Sorting (heapsort, mergesort, quicksort), searching, graph algorithms. Experimental analysis of algorithms also emphasized. Use of computer required.

Not available at this time

Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem.

Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem.

Not available at this time

The course introduces and develops methods for designing and implementing abstract data types using the Java programming language. The main focus is on how to implement abstract data collections and their associated operations. Specific implementations include linked structures, recursive structures, binary trees, balanced trees, and hash tables. Algorithm analysis and asymptotic bounding of implementations is a major topic throughout the course. The topics covered in this course are fundamental to programming and are essential to further computer science courses.