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Stonehill College
320 Washington Street
Easton, MA 02357
508-565-1000

Courses in Computer Science

CS 101 FROM GUTENBERG TO GATES

This course explores the history of technology and its impact on our society. It provides students with the background to understand these changes and the tools they need to manage them, as well as a strong foundation in research, critical thinking, and oral and written communication skills. No prerequisites.
THIS COURSE IS PART OF A LEARNING COMMUNITY WITH SO 212 A GREAT SOCIETY?
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CS 102 BASIC PROGRAMMING 

An introduction to programming for non-majors using Visual Basic .NET
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CS 103 COMPUTER SCIENCE I

Programming in C++, object oriented programming and design. Introduction to algorithms : sorting and searching. Elementary data structures.
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CS 104 COMPUTER SCIENCE II

Continuation of CS 103: introduction to linked lists, stacks, queues, trees.
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CS 195 HOW COMPUTERS WORK

An exploration of how computers work: what goes on inside the computer (hardware), how to program computers (software), the Internet and communication revolution, artificial intelligence and the limits of computation.
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CS 201 - 202 DISCRETE MATHEMATICS FOR COMPUTER SCIEINCE I AND II

Discrete mathematical methods for applications in computer science. Mathematical
induction, graphs, trees, sets, equivalence relations, functions, and partially ordered
sets. Asymptotic complexity, Big-O, and Big Omega, recursion and recurrence equations,
finite and infinite sums. Predicate logic and first order logic. Basic counting methods,
simple combinatorics. Probability and Markov Chains. Linear algebra, applications of
linear algebra in computer science.

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LC 207 MATHEMATICAL EXPERIMENTS IN COMPUTER SCIENCE

This Learning Community course focuses on the delicate balance between theory and practice in computer science, revealing the dual and sometimes contradictory nature of computer science as both an engineering and a mathematical discipline.
This course is an integrative seminar for Discrete Mathematic for Computer Science and Data Structures.  Student who enroll in this course must also enroll in both Discrete Mathematics and Data Structures.   

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CS 211 DATA STRUCTURES

Stacks, queues, linked lists, trees, graphs, searching, and sorting. Design and analysis of algorithms.
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CS 221 COMPUTER LOGIC AND ORGANIZATION

Binary number systems, information representation, Boolean algebra, gates and digital circuit design, timing and control , memory, designing a simple computer, software simulation
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CS 281 ADVANCED PROGRAMMING

Advanced programming and data structure techniques in a language such as Ada, LISP,  Visual C++ or Java.
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CS 304 COMPUTER ARCHITECTURE

The basics of computer organization, architecture and assembly language.  Instructions sets, address modes, and the run/time stack are explored by programming on a RISC machine.  CPU and ALU design, performance analysis, pipelining, cache, virtual memory are examined.  Trade-offs between RISC, CISC and advanced architectures is discussed. Assumes basic knowledge of digital logic. 
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CS 311 ALGORITHMS AND COMPLEXITY

Basic algorithm techniques: recursion, dynamic programming, greedy method branch and bound. Analysis of algorithms: recurrence equations, NP-completeness, asymptotic complexity. Applications include graph and combinatorial algorithms.
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CS 312 COMPILER DESIGN

Finite automata and lexical analysis, context free grammars, top down and bottom up parsing, syntax directed translation, symbol table techniques, runtime storage administration, code generation, optimization.
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CS 314 OPERATING SYSTEMS

Focuses on the fundamentals of operating systems including: processes, deadlocks, memory management, I/O, and file systems. After a thorough grounding in these basics, students will explore distributed/multiprocessor computing. Security and computer networks are also covered. Lectures in class will be reinforced with programming assignments using the Linux operating system.
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CS 323 PROGRAMMING LANGUAGES

Formal language concepts including syntax and basic characteristics of grammars. Control structures, data flow, run-time considerations. Interpretative languages.
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CS 325 DATABASE MANAGEMENT SYSTEMS

This course focuses on the basic principles of Database Management Systems. Students learn why databases are important to the information age. Data Modeling is taught using Entity Relationship diagrams. These data models are then translated into Relational schemas as students learn about Relational Algebra, Calculus, and Relational Database Systems. Practical experience is gained through projects using the commercial RDBMS ORACLE. Students learn SQL (both DDL and DML), database administration, and how to create complete database applications. The course will culminate in a major programming project that demonstrates proficiency in modern database technology. 
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CS 382 ARTIFICIAL INTELLIGENCE

Knowledge representation. Natural language processing. Deduction and inference. Expert Systems. Computer vision. Robotics. Programming in LISP, PROLOG, or another AI language.
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CS 384 THEORY OF COMPUTATION

Introduction to the general theory of computation. Formal grammars: regular, context-free, and context-sensitive languages. Formal automata: finite-state and pushdown models. Decidability. Parsing. Turing theory. The Chomsky hierarchy. Also listed as MA 384.
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CS 390 DATA NETWORKING

Data Networking: Data communications system components, network architectures, layered protocols, traffic analysis and capacity planning
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CS 393 NUMERICAL ANALYSIS

Both theoretical and practical problems in the computational aspects of mathematics: approximation of functions, numerical differentiation, solutions to algebraic and differential equations; topics in linear algebra. Also listed as MA 393
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CS 399 TOPICS IN COMPUTER SCIENCE

Various advanced topics in Computer Science
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CS 400 COMPUTER SCIENCE CAPSTONE

Large-scale software project involving teamwork, written reports, and oral presentations.
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CS 475 INTERNSHIP IN COMPUTER SCIENCE

Opportunity for the qualified student to work in the computer industry under professional supervision.
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CS 490 DIRECTED STUDY IN COMPUTER SCIENCE

Opportunity for upper level students to advanced work in a specialized area of computer science.
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