Course Information
- 2009-2010 Courses:
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CS 108: Life in the Age of Networks
This course investigates how the social, technological, and natural worlds are connected, and how the study of networks sheds light on these connections. A network is a collection of entities linked by some relationship: people connected by friendships (e.g. Facebook); web pages connected by hyperlinks; species connected by the predator-prey relationships. We will emphasize the efficient synthesis and processing of large amounts of data in asking questions about networks in a variety of fields. Topics include: how Google works; "six degrees of separation"; species extinction; the spread of fads through society. No background in computer science or programming is required or expected. No prerequisites. Students who have received credit for Computer Science 111 or above are not eligible to enroll in Computer Science 108. 6; Mathematics and Natural Sciences; offered Fall 2009 -- D. Liben-Nowell -
CS 111: Introduction to Computer Science
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111. No prerequisites. 6; Mathematics and Natural Sciences; offered Fall 2009, Winter 2010, Spring 2010 -- Staff -
CS 201: Data Structures
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that "there has to be a better/smarter way to do this problem?" The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201. Prerequisite: Computer Science 111 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Fall 2009, Winter 2010, Spring 2010 -- Staff -
CS 202: Mathematics of Computer Science
An introduction to some of the mathematical tools crucial to computer science. Topics include logic and proofs; sets, relations, and functions; elementary complexity theory and recurrence relations; basic probability; counting techniques; and graphs. These mathematical tools will be discussed through their application to various topics in computer science, including error-correcting codes, hashing, cryptography, computer graphics, games, and the structure of the Internet and the web. Prerequisites: Mathematics 111; Computer Science 111. 6; Mathematics and Natural Sciences; offered Fall 2009, Spring 2010 -- D. Liben-Nowell -
CS 204: Software Design
It’s easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several medium-sized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of object-oriented design, design patterns, and user interface design. Prerequisite: Computer Science 111 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Winter 2010 -- J. Ondich -
CS 208: Computer Organization and Architecture
Computer processors are extraordinarily complex systems. The fact that they work at all, let alone as reliably as they do, is a monumental achievement of human collaboration. In this course, we will study the structure of computer processors, with attention to digital logic, assembly language, performance evaluation, computer arithmetic, data paths and control, pipelining, and memory hierarchies. Prerequisites: Computer Science 111 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Fall 2009 -- A. Csizmar Dalal -
CS 231: Computer and Network Security
Hackers, phishers, and spammers---at best they annoy us, at worst they disrupt communication systems, steal identities, bring down corporations, and compromise sensitive systems. In this course, we'll study various aspects of computer and network security, focusing mainly on the technical aspects as well as the social and cultural costs of providing (or not providing) security. Topics include cryptography, authentication and identification schemes, intrusion detection, viruses and worms, spam prevention, firewalls, denial of service, electronic commerce, privacy, and usability. Prerequisite: Computer Science 201, 202 or 204 or 208. 6; Mathematics and Natural Sciences; not offered 2009-2010 -
CS 251: Programming Languages
Are there other types of programming languages besides object-oriented ones? This course will survey a number of different programming paradigms in order to do a comparative analysis of features and design. Students will gain experience programming in a variety of programming languages, including functional and logical languages such as Scheme and Prolog. Furthermore, the course will examine such topics in programming language construction as syntax and semantics, mechanisms for parameter passing, typing, scoping, and control structures. Prerequisite: Computer Science 201 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Fall 2009 -- D. Musicant -
CS 252: Algorithms
A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow); applications of those techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example); and computational complexity, particularly NP-completeness, including how to cope algorithmically when confronted with intractable problems. Prerequisites: Computer Science 201; Mathematics 111; Computer Science 202 or Mathematics 236. 6; Mathematics and Natural Sciences; offered Winter 2010 -- D. Liben-Nowell -
CS 254: Automata and Computability
An introduction to the theory of computation, emphasizing an understanding of what problems can and cannot be solved by computers. Topics include formal models of computation, including finite-state automata, pushdown automata, and Turing machines; formal languages, including regular expressions and context-free grammars; and computability and uncomputability. Time permitting, we will discuss computational and mathematical applications, like parsing and Godel's incompleteness theorem. Prerequisites: Computer Science 201; Computer Science 202 or Mathematics 236. 6; Mathematics and Natural Sciences; offered Spring 2010 -- J. Ondich -
CS 311: Computer Graphics
The raster graphics representation of 2- and 3- dimensional images. Topics include frame buffers, data structures for image storage, geometric transformations, hidden surface algorithms, raytracing, splines, and lighting models. Prerequisites: Computer Science 201, Mathematics 232 or consent of the instructor. 6; Mathematics and Natural Sciences; not offered 2009-2010 -
CS 321: Artificial Intelligence
How can we design computer systems with behavior that seems "intelligent?" This course will examine a number of different approaches to this question, including intelligent agents (simulated with a robot), machine learning (including neural networks and genetic algorithms), and reasoning with uncertainty. We will also examine search methods, with an interest in computer game playing. The coursework is a mix of problem solving and computer programming based on the ideas that we discuss. Prerequisite: Computer Science 201 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Spring 2010 -- D. Musicant -
CS 322: Natural Language Processing
Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Lisp). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition. Prerequisites: Computer Science 201 and 202 or permission of the instructor. 6; Mathematics and Natural Sciences; not offered 2009-2010 -
CS 324: Data Mining
How does Google understand what it is you're looking for? How does Amazon.com figure out what items you might want to buy? These questions and others are part of machine learning and data mining, two highly related fields at the crossroads of artificial intelligence, database systems, and statistics. Machine learning concerns itself with getting a computer to learn or discover patterns, whereas data mining focuses this task on large databases. Much of the material will be presented through primary source research papers, and the content will include techniques such as classification, clustering, association rules, web mining, collaborative filtering, and others. Prerequisite: Computer Science 201 or consent of the instructor. 6; Mathematics and Natural Sciences; not offered 2009-2010 -
CS 331: Computer Networks
From the hotspots in coffee shops to the Internet in our homes, computer networking has increasingly pervaded our everyday lives. In this course, we'll study the technical details of computer networks, from local-area to wide-area networks, from the individual connections between machines to networked applications both new and old. Topics include the TCP/IP protocol stack, the OSI reference model, network architecture, protocols and their implementations, routing security, the structure of the Internet, DNS, and emerging applications such as VoIP and peer-to-peer networking. Prerequisite: Computer Science 208 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Fall 2009 -- A. Csizmar-Dalal -
CS 332: Operating Systems
The thing that we call a computer is actually a complex collection of interacting devices. To ensure that these devices work together effectively without excessive human intervention, people have developed operating systems software that coordinates the behavior of the devices and gives programmers ways to control those devices. This course will address the fundamental problems that operating systems need to solve, including those concerned with process management, file organization, memory management, and input/output control. We will also study the structure of the Linux operating system. Prerequisites: Computer Science 208 or consent of the instructor. 6; Mathematics and Natural Sciences; offered Spring 2010 -- J. OndichExtended departmental description for CS 332
If you're working in the lab, you might be editing a file while waiting for a program to compile. Meanwhile, the on-screen clock ticks, a program keeps watch for incoming e-mail, and other users can log onto your machine from elsewhere in the network. Not only that, but if you write a program that reads from a file on the hard drive, you are not expected to concern yourself with turning on the drive's motor or moving the read/write arms to the proper location over the disk's surface. Coordinating all this hardware and software is the job of the operating system.
In this course we will study the fundamental problems faced by operating system designers. We will look at inter-process communication, memory management, file systems, and input/output in general and in the context of particular operating systems. We will also study some parts of the Linux source code.
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CS 334: Database Systems
Database systems are used in almost every aspect of computing, from storing data for websites to maintaining financial information for large corporations. Intrinsically, what is a database system and how does it work? This course takes a two-pronged approach to studying database systems. From a systems perspective, we will look at the low-level details of how a database system works internally, studying such topics as file organization, indexing, sorting techniques, and query optimization. From a theory perspective, we will examine the fundamental ideas behind database systems, such as normal forms and relational algebra. Prerequisite: Computer Science 201 (127) or consent of the instructor. 6; Mathematics and Natural Sciences; offered Winter 2010 -- D. Musicant -
CS 400: Integrative Exercise
Senior Computer Science majors work in teams (typically four to seven students per team) on faculty-specified topics. Required of all senior majors. Prerequisite: Senior standing, Mathematics 121, Computer Science 111, 201, 202 (or Mathematics 236); one course from among Computer Science 204 or 208; two courses from among Computer Science 251, 252 and 254; one course from among Computer Science courses numbered 260 or above or Mathematics 311. 6; S/NC; Does not fulfill a distribution requirement; offered Fall 2009, Winter 2010 -- Staff