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Course Criteria
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4.00 Credits
Spring. Credits: 4. Degree Requirements: Natural Science, F6. An introduction to the fundamental concepts and practices of object-oriented programming. The object-oriented programming paradigm is introduced, with a focus on the definition and use of classes as a basis for fundamental object-oriented program design. Other topics include an overview of programming language principles, simple analysis of algorithms, basic searching and sorting techniques, and an introduction to software engineering issues. Prerequisites: Computer Science 141.
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4.00 Credits
Fall. Credits: 4. Degree Requirements: Natural Science, F6. An introduction to and survey of the mathematics used in computer science including functions, relations, sets, counting, logic, Boolean algebra, proof techniques, induction, recursion, computational complexity, and computability. Other topics may be included as time permits. Prerequisites: Computer Science 141.
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4.00 Credits
Spring. Credits: 4. Degree Requirements: Natural Science, F6. A thorough introduction to the reading, writing, presenting and creating of mathematical proofs. Students will learn and practice in a careful and deliberate way the techniques used to prove mathematical theorems. Proofs studied will be chosen from a variety of fields such as set theory, number theory, analysis, algebra, and graph theory. Topics also include elements of the history and philosophy of mathematics and an introduction to the mathematical community. Prerequisites: Math 122 or permission of instructor.
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4.00 Credits
Fall, Spring. Credits: 4. Degree Requirements: Natural Science, F6. A continuation of Math 122: vector calculus, functions of several variables, partial derivatives, multiple integrals, line integrals, and Green's theorem. Prerequisites: Math 122.
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4.00 Credits
Spring. Credits: 4. Degree Requirements: Natural Science. A bottom-up exploration of the interaction between computer hardware and software. Topics include machine data representation and manipulation, binary file handling, addressing modes and dynamic memory allocation, an introduction to processes and threads, and process memory organization. Key layers of machine abstraction are illustrated through projects that involve an introduction to digital logic, assembly language programming, and an introduction to UNIX system programming. Prerequisites: Computer Science 141.
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4.00 Credits
Fall. Credits: 4. Degree Requirements: Natural Science. An introduction to the fundamental concepts of data structures and the algorithms that arise from them, using the object-oriented design paradigm. Data structures covered include stacks, queues, linked lists, hash tables, trees, and graphs. Other topics include an introduction to iterative and recursive algorithmic strategies and basic algorithm analysis. Corequisite: Computer Science 172 (unless already taken). Prerequisites: Computer Science 142.
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4.00 Credits
Fall. Credits: 4. Degree Requirements: Natural Science, F6. The theory, methods, and applications of ordinary differential equations. Topics include existence, uniqueness and other properties of solutions, linear equations, power series and Laplace transform methods, systems of linear equations, and qualitative analysis. Prerequisites: Math 122.
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4.00 Credits
Spring. Credits: 4. Degree Requirements: Natural Science, F6. Topics include systems of linear equations, matrix algebra, determinants, real and complex vector spaces, linear transformations, eigenvalues and eigenvectors, and diagonalization. Attention is given to proofs. Prerequisites: Math 122.
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4.00 Credits
Fall, Spring. Credits: 4-4. Degree Requirements: Natural Science. Topics include probability spaces, discrete and continuous random variables, independence, expectation, characteristic functions, the Central Limit Theorem, point and interval estimation, hypothesis testing, and regression. (Courses offered in alternate years; scheduled for 2009-2010.) Corequisites: For 311, Math 223. Prerequisites: For 312, Math 311.
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4.00 Credits
Spring. Credits: 4. Degree Requirements: Natural Science. A survey of the special challenges encountered in the development of software for networked computing systems, including security, testing, maintenance, and reliability. Topics include the web as an example of client-server programming, the design and implementation of robust and maintainable web applications, use of multimedia technologies, designing for platform-independence, and programming ethics within the web community. Prerequisites: Computer Science 241.
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