Computer Sciences Commons^™

Privacy Preserving Boosting In The Cloud With Secure Half-Space Queries, Shumin Guo, Keke Chen

Kno.e.sis Publications

This paper presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.

Cs 1010-01: Introduction To Computers And Office Productivity Software, Terri Bauer

Computer Science & Engineering Syllabi

Focus on learning MS Office software applications including intermediate word processing, spreadsheets, database and presentation graphics using a case study approach where critical thinking and problem solving skills are required. Computer concepts are integrated throughout the course to provide an understanding of the basics of computing, the latest technological advances and how they are used in industry. Ethics and issues encountered in business are discussed to challenge students on societal impact of technology.

Cs 1150-01: Introduction To Computer Science, Karen Meyer

Computer Science & Engineering Syllabi

The Introduction to Computer Science course will expose students to the scientific method as implemented in computer science. The course will show students how the scientific method as implemented in computer science can be used as a problem-solving tool. The course requires students to apply and extend the concepts in a laboratory setting. The concepts will include the study of and methodology of algorithm discovery, design, application, and fundamentals of networks. Lecture and Lab

Cs 1160: Introduction To Computer Programming I, Vanessa Starkey

Computer Science & Engineering Syllabi

Basic concepts of computer programming with an emphasis on structured programming techniques. Includes an introduction to object-oriented programing. Integrated lecture/lab.

Cs 1160: Introduction To Computer Programming I, David M. Hutchison

Computer Science & Engineering Syllabi

CS 1160 is the first in a sequence of two programming classes. This course will introduce students to the basic concepts of programming. Examples are from business applications with an emphasis on problem solving with the computer as a tool.

Cs 4800/6800: Web Information Systems, Amit P. Sheth

Computer Science & Engineering Syllabi

No abstract provided.

Cs 7800: Information Retrieval, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course will cover models for information retrieval, techniques for indexing and searching. and algorithms for classification and clustering. It will also cover SVM, latent semantic indexing. link analysis and ranking, Map-Reduce architecture and Hadoop, to different degrees of detail, time permitting.

Cs/Mth 3260/5260: Numerical Methods For Computational Science, Ronald F. Taylor

Computer Science & Engineering Syllabi

Numerical methods for the sciences using modern programming languages. Solution of linear and nonlinear equations, symmetric matrix eigenvalue problems, interpolation, and least squares. Initial value and boundary value problems for representative systems governed by ordinary and partial differential equations are also solved numerically. Three hours lecture.

Cs 3100/5100: Data Structures And Algorithms, Keke Chen

Computer Science & Engineering Syllabi

This course will cover the fundamentals of algorithm design and analysis, the implementation of classical data structures and control structures, and the basic problem solving techniques.

Cs 1180-06: Computer Programming - I, Jay Dejongh

Computer Science & Engineering Syllabi

Basic concepts of programming and programming languages are introduced. Emphasis is on problem solving and object oriented programming. This course provides a general introduction to the fundamentals of computer science and programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours.

Cs 3190: Programming Language Workshop In Python, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course is designed as a self-study in Python. You are expected to learn the language and solve a set of programming problems assigned to you from Budd's Text using Python available from http://www.python.org. There are no exams. We officially meet only once in the quarter. However, l will be available in the posted office hours for clarifications and discussions about the programming problems.

Cs 3100/5100: Data Structures And Algorithms, Meilin Liu

Computer Science & Engineering Syllabi

This is a fundamental course for students majoring in Computer Science. Students will learn: basic algorithm analysis techniques; asymptotic complexity; big-0 and big-Omega notations; efficient algorithms for discrete structures including lists, trees, stacks, and graphs; fundamental computing algorithms including sorting, searching, and hashing techniques.

Cs 1200: Introduction To Discrete Structures, Pascal Hitzler

Computer Science & Engineering Syllabi

No abstract provided.

Cs 2800: Web Design Fundamentals, Mohamed B. Ali

Computer Science & Engineering Syllabi

Introduction to basic web design, development, and information management. Topics include design principles, page layout, hierarchal organization, content management, use of color and graphics, privacy policies, accessibility and site organization. HTML, and modern web programming tools are included in the course.

Cs 1181: Computer Science Ii, Mateen M. Rizki

Computer Science & Engineering Syllabi

This is the second course in a two-semester sequence introducing fundamental concepts and techniques for computer science and engineering. The course focuses on problem analysis, advanced programming concepts using JAVA and fundamental data structures. Students learn to analyze problems and evaluate potential solutions with respect to choice of data structures and computational efficiency. Student are exposed to the underlying implementation of basic data structures available in JAVA libraries and develop the skilled needs to extend existing data structures and design new data structures to solve increasingly complex problems.

Cs 4850/6850: Principles Of Artificial Intelligence, Shaojun Wang

Computer Science & Engineering Syllabi

No abstract provided.

Cs 2160: Visual Basic Programming, Eric Saunders

Computer Science & Engineering Syllabi

This course will cover the fundamentals of object-oriented computer programming; with an emphasis on design, structure, debugging, and testing. Visual Basic 2010 will be used for developing programs.

Cs 7900: Information Security, Meilin Liu

Computer Science & Engineering Syllabi

This course gives a comprehensive study of security vulnerabilities in information systems and the basic techniques for developing secure applications and practicing safe computing. Topics include: Conventional encryption; Data Encryption Standard; Advanced Encryption Standard; Hashing functions and data integrity; Basic Number Theory; Public-key encryption (RSA); Digital signature; Security standards and applications; Access Control; Management and analysis of security. After taking this course, students will have the knowledge of several well-known security standards and their applications; and the students should be able to increase system security and develop secure applications.

Cs 3180/5180: Comparative Languages, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course will introduce fundamental concepts and paradigms underlying the design of modern programming languages. For concreteness, we study the details of an object-oriented language (e.g. Java, C#, C++), a functional language (e.g., Scheme, and get introduced to multiparadigm languages (e.g., Python, Scala). The overall goal is to enable comparison and evaluation of existing languages. The programming assignments will largely be coded in Java and in Scheme, and optionally in Python or Scala.

Cs 4000: Social Implications Of Computing, Leo Finkelstein

Computer Science & Engineering Syllabi

CS 4000 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. In addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class lectures and discussions.

Cs 7720: Data Mining, Guozhu Dong

Computer Science & Engineering Syllabi

This course studies the fundamental concepts, issues, and techniques of data mining. Topics include basics of data, data preprocessing, feature selection/extraction, frequent pattern and association/correlation mining, classification, clustering, outlier analysis, OLAP/OLAM, contrast mining, applications, etc.

Cs 4900/6900-01: Ios Programming, Erik Marlow Buck

Computer Science & Engineering Syllabi

No abstract provided.

Cs 3200/5200: Theoretical Foundations Of Computing, Guozhu Dong

Computer Science & Engineering Syllabi

CS 3200/5200 is an introduction to (a) formal language and automata theory and (b) computability. For (a), we will examine mechanisms for defining syntax of languages and devices for recognizing languages. Along with the fundamentals of these two topics, the course will investigate the relationships between language definition mechanisms and language recognition devices. For (b), we will study decision problems, the Church-Turing thesis, the undecidability of the Halting Problem, and problem reduction and undecidability. The text will be the third edition of Languages and Machines: An Introduction to the Theory of Computer Science, by Thomas Sudkamp.

Cs 4700/6700: Introduction To Database Management Systems, Soon M. Chung

Computer Science & Engineering Syllabi

Survey of logical and physical aspects of database management systems. Entity Relationship and relational models for databases are presented. Physical database design methods, formal DB design concepts, and operating principles of database systems are discussed.

Cs 7840: Soft Computing, John C. Gallagher

Computer Science & Engineering Syllabi

No abstract provided.

Ceg 2170-01: Introduction To C Programming For Engineers, Jay Dejongh

Computer Science & Engineering Syllabi

Basic engineering problem solving using the C programming language. Topics include loops, selection, input/output, files, functions, arrays, complex variables, pointers, structures, and dynamic memory. Students will learn how to approach solving problems in engineering and science; how to develop algorithms, using advanced techniques such as recursion, searching, sorting and linked lists, to solve those problems; and how to implement those algorithms in the C language.

Ceg 7550-01: Computer Vision, Arthur A. Goshtasby

Computer Science & Engineering Syllabi

This course covers basic algorithms for low-level mid-level and high-level vision. The algorithms deal with edge detection and linage segmentation, feature detection and matching, and object recognition Specific topics covered in the course are:

Contents: The following topics will be covered.
1. Introduction
2. Image formation
3. Linear filtering
4. Feature detection and matching
5. Image segmentation
6. Feature--based alignment
7. Image stitching
8. Structure from Motion
9. Dense motion estimation
10. Stereo correspondence
11. 3-D reconstruction
12. Recognition

Ceg 3320-01: Digital System Design, Travis E. Doom

Computer Science & Engineering Syllabi

Basics of Digital Computer Hardware and Design. Topics include switching algebra and switching functions, logic design of combinational and sequential circuits, storage elements, register-level design, and instrumentation. 3 hours lecture, 1 credit hour lab.

Ceg 2400-01: Intro To Pc Networking, Chris P. Fickert

Computer Science & Engineering Syllabi

Introduction to networking technologies including infrastructure and architectures, standards, protocols and directory services, administration, security and management. Integrated lecture and lab.

Ceg 3110/5100-01: Introduction To Software Testing, John A. Reisner

Computer Science & Engineering Syllabi

This course covers software testing strategies, along with established best practices, so students learn how to test their software in a complete and systematic (vice ad-hoc) manner. Particular attention is paid to planning, writing, and executing software tests, along with associated documentation, (i.e., a software test plan), which includes documented results. Various projects are assigned, designed to illustrate various challenges associated with software testing, and to reinforce the strategies and techniques used to overcome these challenges.