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CSCI 201: Digital Electronics and Microcomputers
4.00 Credits
Susquehanna University
Basic fundamentals of electronics. Uses Boolean Algebra to develop the concepts of logic gates, memory elements, sequential logic, arithmetic elements, ROM and RAM. Combines elements to analyze microcomputer design. Same as PHYS:201. 4 SH. 3 lecture hours. 3 laboratory hours.
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CSCI 282: Computer Organization
4.00 Credits
Susquehanna University
Fundamentals of computer organization and machine architecture. Presents an overview of computer system organization and examines in detail the digital logic level, the register level, and the operating system program interface. Uses the assembly language of an available machine for programming assignments. Prerequisite: CSCI:281 Data Structures or permission of instructor. 4 SH.
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CSCI 351: Numerical Computing
2.00 Credits
Susquehanna University
An introduction to the computational techniques for solving mathematical problems. Topics include roots of non-linear equations, interpolation, numerical differentiation and integration, and numerical solutions of differential equations. Same as MATH:351. Prerequisites: MATH:111 Calculus I; MATH:112 Calculus II is suggested. 2 SH.
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CSCI 352: Numerical Analysis
2.00 Credits
Susquehanna University
Theoretical study of the standard numerical techniques for solving mathematical problems. Topics include roots of non-linear equations, polynomial interpolation, solving systems of equations, numerical integration and numerical solutions of differential equations. Same as MATH:352. Prerequisites: CSCI:351 Numerical Computing, MATH:112 Calculus II, MATH:201 Linear Algebra. 2 SH.
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CSCI 355: Operations Research
4.00 Credits
Susquehanna University
Mathematical models and optimization techniques useful in decision making. Includes linear programming, game theory, integer programming, queuing theory, inventory theory, networks and reliability. Further topics, such as non-linear programming and Markov chains, as time permits. Same as MATH:355. Prerequisites: MATH:112 Calculus II, MATH:201 Linear Algebra and MATH:141 Introduction to Statistics, MATH:221 Discrete Structures, or permission of instructor. 4 SH.
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CSCI 355 - Operations Research
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CSCI 370: Cryptology and Number Theory
4.00 Credits
Susquehanna University
Cryptology is the study of hiding the meaning of messages. Cryptology is an interesting venue for the study of its mathematical underpinnings (number theory, matrix algebra, probability and statistics) and as an opportunity to implement techniques by means of computer programs. We will consider monoalphabetic and polyalphabetic encryptions, public key cryptography, security, and anonymity. Same as MATH:370. Prerequisite: MATH:221 Discrete Structures. 4 SH.
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CSCI 370 - Cryptology and Number Theory
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CSCI 381: Algorithms
4.00 Credits
Susquehanna University
Introduces the design and implementation of algorithms using an object-oriented programming language such as C++ or Java. Covers correctness and efficiency of algorithms for sorting, searching, graph problems and mathematical algorithms. Prerequisites: MATH:221 Discrete Structures, CSCI:281 Data Structures. 4 SH.
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CSCI 391: Data Communications and Networks I
2.00 Credits
Susquehanna University
An overview of data communications and networks, including channel capacity, Ethernet, Internet protocols, DHCP, DNS, TCP, FTP, SMTP, HTTP, web servers, and file sharing. Prerequisite: CSCI:181 Principles of Computer Science. 2 SH.
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CSCI 392: Data Communications and Networks II
2.00 Credits
Susquehanna University
Further topics in networks, with an emphasis on security. Includes authentication, encryption, verification, certificates, digital signatures, attacks and defenses, privacy, and anonymity. Also covers current developments in networks. Prerequisite: CSCI:391 Data Communications and Networks I. 2 SH.
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CSCI 434: Artificial Life
2.00 Credits
Susquehanna University
Science and mathematics describe natural phenomena so well that lines between real world events and the corresponding theoretical world events have become blurred. Can computer models simulate key characteristics of life, such as behavior, motivation, reproduction, adaptation, perception, and even intelligence? Proponents of strong artificial life believe that computers will eventually serve not only to model life processes but will actually think and be alive. These contentions will be compared and contrasted with an emphasis on the current status and future implications of strong artificial life. This course is meant to be accessible to both majors and non-majors. Same as MATH:434. Prerequisites: junior or senior standing and completion of the Mathematics/Logic and Science and Technology Core requirements. Does not count for mathematics or computer science major credit. 2 SH.
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