| source University of Illinois at Urbana-Champaign (X) |
level |
department Computer Science (X) |
Introduction to Computer Science as a field and career for computer science majors. Overview of the field is presented along with specific examples of problem areas and methods of solution. Recommended for all freshman Computer Science majors.
Score: 6.597577 Details | Listing | Web page
Fundamental principles, concepts, and methods of computing, with emphasis on applications in the physical sciences and engineering. Basic problem solving and programming techniques; fundamental algorithms and data structures; use of computers in solving engineering and scientific problems. Intended for engineering and science majors. Prerequisite:
Score: 6.597577 Details | Listing | Web page
Same as
Score: 6.597577 Details | Listing | Web page
Same as
Score: 6.597577 Details | Listing | Web page
Introduction to computing as an essential tool of academic and professional activities. Functions and interrelationships of computer system components: hardware, systems and applications software, and networks. Widely used application packages such as spreadsheets and databases. Concepts and practice of programming for the solution of simple problems in different application areas. Intended for non-science and non-engineering majors. Prerequisite:
Score: 6.597577 Details | Listing | Web page
Practical laboratory experience in the methods used and skills required for writing and maintaining well-structured software. Extensive practice with a programming language. Different sections use different programming languages. An existing knowledge of fundamental computing principles is assumed. Three laboratory hours per week. Credit is not given for studying a specific language more than once. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Introduces basic concepts in computing and fundamental techniques for solving computational problems. Intended as a first course for computer science majors and others with a deep interest in computing. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Examines discrete mathematical structures frequently encountered in the study of Computer Science. Topics will include sets, propositions, boolean algebra, induction, recursion, relations, functions, and graphs. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Offered for honors credit in conjunction with other 100-level computer science courses taken concurrently. A special examination may be required for admission to this course. May be repeated. Prerequisite: Concurrent registration in another 100-level computer science course (see Schedule).
Score: 6.597577 Details | Listing | Web page
May be repeated.
Score: 6.597577 Details | Listing | Web page
Ethics for the computing profession. Ethical decision-making; licensing; intellectual property, freedom of information, and privacy. Includes oral presentations. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Data abstractions: elementary data structures: lists, stacks, queues, trees; searching and sorting techniques. Introduction to the principles of software engineering including term programming project. Prerequisite:
Score: 6.597577 Details | Listing | Web page
Introduction to computer architecture, working up from the logic gate level: combinational and sequential networks; computer arithmetic; arithmetic/logic units; memory organization; control unit design. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Second-level course in computer architecture. Machine-level programming, instruction sets, data representations; subroutines; input/output hardware and software; linking and loading; relation to high-level languages. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Covers the basics of system programming, including POSIX processes, process control, inter-process communication, synchronization, signals, simple memory management, file I/O and directories, shell programming, socket network programming, RPC programming in distributed systems, basic security mechanisms, and standard tools for systems programming such as debugging tools. Credit is not given for both
Score: 6.597577 Details | Listing | Web page
Intensive programming lab intended to strengthen skills in programming. Prerequisite:
Score: 6.597577 Details | Listing | Web page
Group projects for honors credit in computer science. Sections of this course are offered in conjunction with other 200-level computer science courses taken concurrently. A special examination may be required for admission to this course. May be repeated. Prerequisite: Concurrent registration in another 200-level computer science course (see Schedule).
Score: 6.597577 Details | Listing | Web page
Introduction to numerical methods for students in science and engineering; topics include floating-point computation, systems of linear equations, approximation of functions and integrals, the single nonlinear equation, and the numerical solution of ordinary differential equations; discusses various applications in science and engineering; includes some programming as well as the use of high quality mathematical library routines. Same as
Score: 6.597577 Details | Listing | Web page
Finite automata and regular languages; pushdown automata and context-free languages; Turing machines and recursively enumerable sets; computability and the halting problem; undecidable problems. Prerequisite:
Score: 6.597577 Details | Listing | Web page
May be repeated. Prerequisite: Consent of instructor.
Score: 6.597577 Details | Listing | Web page
Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. May be repeated in the same or separate terms if topics vary.
Score: 6.597577 Details | Listing | Web page
Integrates software engineering principles with data structures implemented in C++. Covers software engineering in three stages: personal software process (checkpoints, project plans, defects, and code reviews), prior to coding (process models, requirements, and design), and after coding (testing and quality assurance techniques). The concepts, principles, and use of data structures will include pointers, lists, arrays, sets, stacks, trees, hashing, graphs, priority queues, and sorting. Special emphasis will be placed on the implementations of these structures in real-world applications. While prior experience with either C, C++, or Java is assumed, C++ is taught in the first three weeks. Same as
Score: 6.597577 Details | Listing | Web page
Introduction to the theory, design, and implementation of text-based information systems. Text analysis, retrieval models (e.g., Boolean, vector space, probabilistic), text categorization, text filtering, clustering, retrieval system design and implementation, and applications to web information management. Same as
Score: 6.597577 Details | Listing | Web page
Examines the logical organization of databases: the entity-relationship model; the hierarchical, network, and relational data models and their languages. Functional dependencies and normal forms. Design, implementation, and optimization of query languages; security and integrity; concurrency control, and distributed database systems. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite:
Score: 6.597577 Details | Listing | Web page
Introduction to the concepts, techniques, and systems of data warehousing and data mining. Design and implementation of data warehouse and on-line analytical processing (OLAP) systems; data mining concepts, methods, systems, implementations, and applications. 3 undergraduate or graduate hours. 4 graduate hours. Prerequisite:
Score: 6.597577 Details | Listing | Web page