Courses in Computer Science (Division 353)

Introduction to Computing Courses

CS 100 is an intro class intended for students who plan to major in Computer Science, Computer Engineering or Electrical Engineering. It is not a class for students who are looking for a good general introduction for computing.

Computer Science does offer two classes intended for non-majors: CS181, Intro to Computing and CS 183, Elementary Programming Concepts. These classes are much more appropriate for entering LS&A students who plan on majoring in areas other than Computer Science.

What should I take for my first computing course?

  1. CS 181 learn how to use basic computer software packages like word processing, spreadsheets, simple graphics and databases, etc. (not programming). Does not count for the computing requirement in Electrical Engineering or Computer Engineering free elective only.
  2. CS 183 learn the fundamentals of C++ programming (including C programming). Usually taken by LS&A students who do not plan to major in computer science (CS) or computer engineering (CE). Assumes no prior programming experience. Does not count for the computing requirement in Electrical Engineering or Computer Engineering free elective only.
  3. Engineering 101 learn the fundamentals of C programming plus engineering applications of computing, including MATLAB. Usually taken by engineering students who do not plan to major in Electrical Engineering, Computer Engineering, or Computer Science. This course replaces the former Engineering 103, 104, 106, 107 courses. Assumes no prior programming experience.
    Note: this course is counted as non-LS&A credit. (There is a limit of 12 credits in the 120 required for an LS&A degree.)
  4. CS 100 recommended first course for those who intend to major in electrical engineering, computer science or computer engineering. It assumes no prior programming experience. Half the course is devoted to computer hardware components and the second half to the basics of programming using C. If you take EECS/CS 183 or Engineering 101 and then decide later you want to be an Electrical Engineering, Computer Engineering, or Computer Science major, you can take a bridge course to pick up the hardware half of EECS/CS 100 for one credit; you do not have to take all of EECS/CS 100.
  5. If you already have C experience and want to jump to the next programming course, you need to take the EECS/CS 100 bridge course (for Fall 1997 it is listed as EECS/CS 284 section 3), and then enroll in EECS/CS 280.


If you are interested in becoming an Electrical Engineering or Computer Engineering major, contact the EECS Counseling Office at 763-2305, 3415 EECS Building.

If you are interested in becoming a Computer Science concentrator, contact the LS&A Academic Advising Center at 764-0332, 1255 Angell Hall.

If you are undecided about which of these three options to choose, please contact the College of Engineering Freshman Counseling Office at 647-7106, 1009 Lurie Engineering Center.

100/EECS 100. Introduction to Computing Systems. (4). (MSA). (BS).

How a computer works, from the machine level to high level programming. Circuits, instructions, memory, data. Assembly language. Binary arithmetic, data types, data structures. Translation of high level languages. The C programming language: data structures, control, iteration, recursion. Basic algorithm analysis.
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181/EECS 181. Introduction to Computer Systems. Credit is granted for only one course among CS 181, Engin. 103, and Engin. 104. (4). (Excl). (BS).

Introduces students to computers. Focuses on software, hardware, and social impact of computers. Elementary programming concepts, software packages and applications, word processing, data communications, information management, input-output, data entry, computer hardware components and storage devices, microcomputers, and ethics in computing. Programming assignments using a personal computer. Term paper required.
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183/EECS 183. Elementary Programming Concepts. This course is not intended for computer science concentrators or computer engineering concentrators. Credit is granted for only one course among CS 183, Engin. 103, and Engin. 104. (4). (MSA). (BS).

Introduction to a high level programming language, top down analysis, and structured programming. Basic searching and sorting techniques. No previous experience in computers or programming is assumed. Students will write and debug several computer programs.
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210/EECS 210. Electrical Engineering I. Math. 116. Credit is not granted for both CS 210 and EECS 314. (4). (Excl). (BS).

Introductory electrial engineering topics: audio signals and their processing; basics of electricity; elementary circuit design and analysis. Frequency content of signals, Fourier series, filtering. Analysis of resistive circuits. Steady-state response of circuits of resistors, capacitors, inductors and operational amplifiers to sinusoidal signals (frequency response). Laboratory experience with electrical signals and circuits.
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211/EECS 211. Electrical Engineering II. CS 210, and prior or concurrent enrollment in Math. 216. Credit is not granted for both CS 211 and EECS 313. (4). (Excl). (BS).

Introductory electrial engineering topics, continued: basic circuit analysis; elementary transistor and diode circuits. Transient analysis of circuits. Introduction to diode and transistor circuits. Amplifiers, limiters, filters and logic circuits. Laboratory experience with electrical signals and circuits.
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270/EECS 270. Introduction to Logic Design. CS 100. (4). (MSA). (BS).
Binary number systems, switching algebra, digital design techniques, logic gates, logic minimization, standard combinational circuits, sequential circuits, latches and flip-flops, synthesis of synchronous sequential circuits, PLAs, ROMs, RAMs, arithmetic circuits, introduction to computer organization, data path design, control of complex operations, computer-aided design. Laboratory includes hardware design and CAD experiments. OBJECTIVE: Develop engineering skills in the design and analysis of digital logic circuits with applications to digital computers. TEXTBOOK AND SUPPLIES: J. P. Hayes, Introduction to Digital Logic Design (Addison-Wesley); Course Pack (Copy Center in Pierpont Commons); REFERENCES On reserve at the Media Union. You must be registered in the lecture (Sec. 001 or 002) that you attend. EXAMINATIONS: Two 1-hour evening closed book multiple-choice examinations plus one 2-hour final examination, covering topics from lectures, lab material, homework, and text reading assignments No textbook, reference books, homework set solutions, notes, lab papers, calculators, or the like are permitted. GRADING: Lab Grade, 30%; Exams, 30%; Final exam, 30%; Homework, 10%. Graded on a curve. The average final grade in the course typically ranges from C+ to B. WL:3 (Getty, Lomax)
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280/EECS 280. Programming and Introductory Data Structures. Math. 115 and CS 100. Two credits granted to those who have completed CS 283. (4). (MSA). (BS).
Techniques and algorithm development and effective programming, top-down analysis, structured programming, testing, and program correctness. Program language syntax and static and run-time semantics. Scope, procedure instantiation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees.
Course format and attendance: There are three lectures per week, one discussion session per week, and there are weekly reading assignments from the textbooks. The purpose of the lectures and the discussion sessions is to explain the required material and to answer student questions. You are expected to have studied the textbook material yourself prior to, or at least during, the lectures on each subject. There will be several programming projects, a midterm exam, and a final exam; their due dates are given later in this syllabus. The two lecture sections of this course are being team-taught by the two professors listed below. The course material and policies are the same for each of the two sections of the course. If you must miss one of the lectures, you should be able to get the (almost) identical content by attending the other lecture section on the same day. You should plan on attending the lectures and discussion sections regularly. You may choose not to attend, but you are responsible for all material and announcements presented in the lectures and in the discussion sections. You are not entitled to a private presentation of a lecture or a discussion that you chose to skip. Please note that material not in the textbooks will often be presented in lecture or discussion; you are responsible for this material, in addition to the material in the assigned readings. The bulk of your course grade (70%) will come from the course programming projects; midterm exam 10%, Final exam 20%. (Flanigan, Kieras)
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284/EECS 284. Introduction to a Programming Language or System. Some programming knowledge is required. No credit granted for the C minicourse to those students who have completed CS 280. (1). (Excl). (BS).

A mini course covering the fundamentals of a high level programming language or a system such as UNIX. Programming problems will be assigned. Specific languages or systems to be offered will be announced in advance. Credit will not be given for the C mini course to students who have taken EECS 280.
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303/EECS 303. Discrete Structures. Math. 115. (4). (MSA). (BS).

Fundamental concepts of algebra; partially ordered sets, lattices, Boolean algebras, semigroups, rings, and polynomial rings. Graphical representation of algebraic systems; graphs, directed graphs. Application of these concepts to various areas of computer engineering.
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370/EECS 370. Introduction to Computer Organization. CS 270 and CS 280. (4). (Excl). (BS).

Computer organization will be presented as a hierarchy of virtual machines representing the different abstractions from which computers can be viewed. These include the logic level, microprogramming level, and assembly language level. Lab experiments will explore the design of a microprogrammed computer.
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380/EECS 380. Data Structures and Algorithms. CS 280 and CS 303. (4). (NS). (BS).

Abstract data types. Recurrence relations and recursions. Advanced data structures: sparse matrices, generalized lists, strings. Tree-searching algorithms, graph algorithms general searching and sorting. Dynamic storage management. Analysis of algorithms O-notation. Complexity. Top-down program development: design, implementation, testing modularity. Several programming assignments.
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398/EECS 398. Special Topics. Permission of instructor. (1-4). (Excl).

Topics of current interest selected by the faculty. Lecture, seminar, or laboratory.
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400/EECS 400/Math. 419. Linear Spaces and Matrix Theory. Four terms of college mathematics beyond Math. 110. No credit granted to those who have completed or are enrolled in Math. 217 or Math. 513. One credit granted to those who have completed Math. 417. (3). (Excl). (BS).

See Mathematics 419.
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442/EECS 442. Computer Vision. CS 380. (4). (Excl). (BS).

Computational methods for the recovery, representation, and application of visual information. Topics from image formation, binary images, digital geometry, similarity and dissimilarity detection, matching, curve and surface fitting, constraint propagation and relaxation labeling, stereo, shading texture, object representation and recognition, dynamic scene analysis, and knowledge based techniques. Hardware/software techniques.
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470/EECS 470. Computer Architecture. CS 370. (4). (Excl). (BS).

Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queueing models. CPU architecture. Instruction sets. ALU design. Hardware and microprogrammed control. Nanoprogramming. Memory hierarchies. Virtual memory. Cache design. Input-output architectures. Interrupts and DMA. I/O processors. Parallel processing. Pipelined processors. Multiprocessors.
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476/EECS 476. Foundations of Computer Science. CS 280 and 303. (4). (Excl). (BS).

An introduction to computation theory: finite automata, regular languages, pushdown automata, context-free languages, Turing machines, recursive languages and functions, and computational complexity.
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477/EECS 477. Introduction to Algorithms. CS 380. (4). (Excl). (BS).

Fundamental techniques for designing efficient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divide-and-conquer, greedy methods, graph search techniques, dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.
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478/EECS 478. Logic Circuit Synthesis and Optimization. CS 270 and CS 303, and senior or graduate standing. (4). (Excl). (BS).

Advanced design of logic circuits. Technology constraints. Theoretical foundations. Computer-aided design algorithms. Two-level and multilevel optimization of combinational circuits. Optimization of finite-state machines. High-level synthesis techniques: modeling, scheduling, and binding. Verification of testing.
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481/EECS 481. Software Engineering. CS 380. (4). (Excl). (BS).

Pragmatic aspects of the production of software systems, dealing with structuring principles, design methodologies and informal analysis. Emphasis is given to development of large, complex software systems. A term project is usually required.
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482/EECS 482. Introduction to Operating Systems. CS 370 and 380. (4). (Excl). (BS).

Operating system functions and implementations: multi-tasking; concurrency and synchronization; deadlock; scheduling; resource allocation; real and virtual memory management; input/output; file systems. Students write several substantial programs dealing with concurrency and synchronization in a multitasking environment.
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483/EECS 483. Compiler Construction. CS 380 and 476. (4). (Excl). (BS).

Introduction to compiling techniques including parsing algorithms, semantic processing, and optimization. Students implement a compiler for a substantial programming language using a compiler generating system.
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484/EECS 484/IOE 484. Database Management Systems. CS 380 or IOE 373. (4). (Excl). (BS).
Concepts and methods for the design, creation, query, and management of large enterprise databases. Functions and characteristics of the leading database management systems. Query languages such as SQL, forms, embedded SQL, and application development tools. Database design, normalization, access methods, query optimization, transaction management and concurrency control, recovery, and integrity.
Database systems deal with the management of the large quantities of data that are needed for virtually any important computing environment. These systems handle the important issues concerning data in order that the applications need not have to do so. Database technology is already well-established in terms of numerous application areas, but its increasing importance, several emerging technologies, and many unresolved problems, continue to spur the research and development efforts in the area. The objective of this course is to study the established basic technology issues for databases. We will examine both the users' perspective as well as the database implementor's perspective in this course. Students need to know the basics of computer architecture, programming, algorithms, and operating systems. Required Reading: (1) Korth H.F., Silberschatz A., and Sudarshan, S. Database System Concepts, 3rd Ed., McGraw-Hill. (2) Handouts. Recommended Reading: (1) Ramakrishnan, R. Database Management Systems, 1997, McGraw-Hill. (2) Teorey,T.J. Database Modeling and Design: The Fundamental Principles, 2nd Edition, Morgan Kaufmann Pub., San Francisco, CA, 1994. (Soparkar)
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487/EECS 487. Interactive Computer Graphics. CS 380 and senior standing. (4). (Excl). (BS).

Graphics devices and fundamentals of operation. Two dimensional and three dimensional transformations. Interactive graphical techniques and applications. Three dimensional graphics, perspective transformation, hidden line elimination. Data structures and languages for graphics. Interactive graphical programming.
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492/EECS 492. Introduction to Artificial Intelligence. CS 380. (4). (Excl). (BS).

Fundamental concepts of AI, organized around the task of building computational agents. Core topics include search, logic, representation and reasoning, automated planning, decision making under uncertainty, and machine learning.
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493/EECS 493. User Interface Design and Analysis. CS 481. (3). (Excl). (BS).

Current theory and design techniques concerning how user interfaces for computer systems should be designed to be easy to learn and use. Focus on cognitive factors, such as the amount of learning required, and the information-processing load imposed on the user, rather than ergonomic factors.
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494/EECS 494. Computer Game Design and Development. CS 380. (4). (Excl).

The purpose of this course is to give the students a rigorous introduction to the techniques and design principles of computer game development. This course forces students to integrate many computer science and engineering concepts. In terms of design, we emphasize the constraints that come from high-speed interactions with human users and study material in human-interface design, computer algorithms and data structures (such as binary-space partition trees), optimization techniques, artificial intelligence techniques, story and plot coherence, and game play. For development we study software engineering techniques, object oriented design and implementation, existing software development environments, and the legalities and economics of creating commercial software. Overall we emphasize the importance of design before implementation, as well as building on existing software packages. (Laird)
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500. Special Study. Graduate or undergraduate concentration in Computer Science; and permission of instructor. (1-6). (Excl). (INDEPENDENT). May be repeated for credit.

Special reading and study in particular areas of computer science for advanced undergraduates and beginning graduate students. Each student is provided with the proper section number by the staff member with whom the work has been arranged. Students are responsible for getting properly registered for this course.
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505/EECS 505/Math. 562/Aero. 577/IOE 511. Continuous Optimization Methods. Math. 217, 417 or 419. (3). (Excl). (BS).

See Mathematics 562.
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543/EECS 543. Knowledge-Based Systems. CS 492 and permission of instructor. (3). (Excl). (BS).

Techniques and principles for developing application software based on explicit representation and manipulation of domain knowledge, as applied to computer vision, robotic control, design and manufacturing, diagnostics, autonomous systems, etc. Topics include: identifying and representing knowledge, integrating knowledge-based behavior into complex systems, reasoning, and handling uncertainty and unpredictability.
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570/EECS 570. Parallel Computer Architecture. CS 470. (3). (Excl). (BS).

Pipelining and operation overlapping, SIMD and MIMD architectures, numeric and non-numeric applications, VLSI, WSI architectures for parallel computing, performance evaluation. Case studies and term projects.
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571/EECS 571. Principles of Real-Time Computing. CS 470 and CS 482. (3). (Excl). (BS).

Principles of real-time computing based on high performance, ultra reliability and environmental interface. Architectures, algorithms, operating systems, and applications that deal with time as the most important resource. Real-time scheduling, communications, and performance evaluation.
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574/EECS 574. Theoretical Computer Science I. CS 476. (4). (Excl). (BS).

Fundamentals of the theory of computation and complexity theory. Computability, undecidability, and logic. Relations between complexity classes, NP-completeness, P-completeness, and randomized computation. Applications in selected areas such as cryptography, logic programming, theorem proving, approximation of optimization problems, or parallel computing.
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583/EECS 583. Programming Languages. CS 476 and CS 483. (4). (Excl). (BS).

Various programming languages are compared to understand general principles. To do this systematically and ignore inessential details, a formal specification method is introduced. Current programming paradigms are examined; their potentials and compatibility are assessed. For example, the question why functional languages become imperative when they "go public" is discussed.
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589/EECS 589. Advanced Computer Networks. CS 489. (4). (Excl). (BS).

Advanced topics and research issues in computer networks. Topics include routing protocols, multicast delivery, congestion control, quality of service support, network security, pricing and accounting, and wireless access and mobile networking. Emphasis is placed on performance trade-offs in protocol and architecture designs. Readings assigned from research publications. A course project allows in-depth exploration of topics of interest.
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595/EECS 595/Ling. 541. Natural Language Processing. Senior standing. (3). (Excl). (BS).

A survey of syntactic and semantic theories of natural language processing, including unification-based grammars, methods of parsing, and a wide range of semantic theories from artificial intelligence as well as from philosophy of language. Programming is optional though a project is normally required.
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598/EECS 598. Special Topics in Electrical Engineering and Computer Science. Permission of instructor or advisor. (1-4). (Excl). (BS). May be repeated for credit.

Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.
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