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Rensselaer Catalog 2017-2018 [Archived Catalog]
Courses
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CSCI 4270 - Computational Vision
The goal of this course is to introduce students to the problems, challenges, and applications of computer vision from a computational perspective. Topics include camera modeling and image formation, feature extraction, object and face recognition, image mosaic construction, stereo and three-dimensional imaging, motion, and tracking. Machine learning methods, including deep convolutional neural networks, will be studied and applied throughout the course. Students cannot receive credit for both CSCI 4270 and CSCI 6270.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and MATH 2010 or permission of instructor.
When Offered: Fall term odd-numbered years.
Cross Listed: CSCI 6270.
Credit Hours: 4
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CSCI 4320 - Parallel Programming
Techniques and methods for parallel programming: models of parallel machines and programs, efficiency and complexity of parallel algorithms. Paradigms of parallel programming and corresponding extensions to sequential programming languages. Overview of parallel languages and coordination languages and models; programming on networks of workstations. Basic parallel algorithms: elementary computation, matrix multiplication, sorting; sample scientific application. Students cannot receive credit for both CSCI 4320 and CSCI 6360.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and either CSCI 2500 or ECSE 2660.
When Offered: Spring term annually.
Cross Listed: CSCI 6360.
Credit Hours: 4
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CSCI 4340 - Ontologies
This course provides an introduction to ontologies, their uses, and an overview of their application in semantically enabled systems. Ontologies encode term meanings and are used to improve communication and enable computer programs to function more effectively. Class participants learn how to use ontologies in web-based applications and evaluate ontologies for reuse. Participants read relevant papers, learn how to critically review ontology papers and ontologies, and participate in group project(s) designing, using, and evaluating ontologies. Students cannot receive credit for both CSCI 4340 and CSCI 6340.
Prerequisites/Corequisites: Prerequisite: CSCI 2300.
When Offered: Spring term annually.
Cross Listed: CSCI 6340.
Credit Hours: 4
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CSCI 4350 - Data Science
Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity, and heterogeneity of data being made available over the Internet. It combines aspects of data management, library science, computer science, and physical science. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught.
Prerequisites/Corequisites: Data Structures (CSCI 1200), Database Systems (CSCI 4380) preferred.
When Offered: Fall term annually.
Cross Listed: Cross listed as ITWS 4350/6350, CSCI 6350 and ERTH 4350/6350. Students can obtain credits for only one of these courses.
Credit Hours: 3
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CSCI 4370 - Data and Society
Data and Society provides a broad overview of how society is leveraging and responding to the social, organizational, policy, and technical opportunities and challenges of a data-driven world. Course themes focus on various aspects of the data ecosystem, data and innovation, and data and the broader community. Assignments build writing, presentation, and critical thinking, and assessment skills, all of which are important for professional success. This is a communication-intensive course.
Prerequisites/Corequisites: CSCI 4350/6350 or ITWS 4350/6350 or permission of instructor.
When Offered: Spring term annually.
Cross Listed: CSCI 6370. Students cannot receive credit for both CSCI 4370 and CSCI 6370.
Credit Hours: 4
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CSCI 4380 - Database Systems
Discussion of the state of practice in modern database systems, with an emphasis on relational systems. Topics include database design, database system architecture, SQL, normalization techniques, storage structures, query processing, concurrency control, recovery, security, and new directions such as object-oriented and distributed database systems. Students gain hands-on experience with commercial database systems and interface building tools. Programming projects are required.
Prerequisites/Corequisites: Prerequisite: CSCI 2300.
When Offered: Spring term annually.
Credit Hours: 4
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CSCI 4390 - Data Mining
This course will provide an introductory survey of the main topics in data mining and knowledge discovery in databases (KDD), including: classification, clustering, association rules, sequence mining, similarity search, deviation detection, and so on. Emphasis will be on the algorithmic and system issues in KDD, as well as on applications such as Web mining, multimedia mining, bioinformatics, geographical information systems, etc. Students cannot receive credit for both CSCI 4390 and CSCI 6390.
Prerequisites/Corequisites: Prerequisites: CSCI 2300.
When Offered: Fall term annually.
Cross Listed: CSCI 6390.
Credit Hours: 4
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CSCI 4400 - Xinformatics
Informatics covers a broad range of disciplines addressing challenges in the explosion of data and information resources. Xinformatics provides commonality for implementations in specific disciplines, e.g. X=astro, geo. Informatics’ theoretical bases are information and computer science, cognitive science, social science, library science, aggregating these studies and adding the practice of information processing, and the engineering of information systems. This course grounds the material that students will learn in discipline areas by coursework and project assignments. Note: Students cannot obtain credit for both this course and ITWS 4400 or ITWS 6400.
Prerequisites/Corequisites: CSCI 1200 and Data Science (CSCI/ERTH/ITWS 496x/696x).
When Offered: Spring term annually.
Cross Listed: Cross listed as ITWS 6400, CSCI 6400 and ERTH 4400/6400. Students can only obtain credit for one of these courses.
Credit Hours: 3
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CSCI 4430 - Programming Languages
This course is a study of the important concepts found in current programming languages. Topics include language processing (lexical analysis, parsing, type-checking, interpretation and compilation, run-time environment), the role of abstraction (data abstraction and control abstraction), programming paradigms (procedural, functional, object-oriented, logic-oriented, generic), and formal language definition. Students cannot receive credit for both CSCI 4430 and CSCI 6430.
Prerequisites/Corequisites: Prerequisite: CSCI 2300 and CSCI 2600.
When Offered: Fall term annually.
Cross Listed: CSCI 6430.
Credit Hours: 4
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CSCI 4440 - Software Design and Documentation
Software system design methodology emphasizing use of object oriented modeling of application domains and of software systems, and emphasizing the roles of written and oral communication in software engineering. Project management and software testing. Individual and team projects include specification, software architecture, user interfaces, and documentation of the phases of a project. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisite: CSCI 2300.
When Offered: Fall and spring terms annually.
Credit Hours: 4
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CSCI 4450 - Principles of Program Analysis
The goal of this course is to introduce students to program analysis and its many applications in software engineering, particularly in improving software quality and software productivity. Concretely, students who successfully complete this course should be able to: (1) understand and apply program analysis techniques, such as dataflow analysis and type-based analysis; (2) implement program analysis; (3) understand and apply software testing techniques, such as black-box testing and white-box testing; and (4) understand and apply refactoring techniques.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and CSCI 2600.
When Offered: Spring term even-numbered years.
Cross Listed: CSCI 6450. Students cannot receive credit for both CSCI 4450 and CSCI 6450.
Credit Hours: 4
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CSCI 4490 - Robotics II
This course introduces methods that leverage the basic analysis techniques learned in Robotics I to develop numerical and algorithmic techniques needed to endow robots with the “intelligence” to devise strategies to solve problems they will encounter. Once these abilities are sufficiently well developed, robots will become safe and autonomous, thus paving the way for pervasive personal robots. Topics include: configuration space representation, cell decomposition, roadmap methods, rapidly-exploring random trees, simultaneous localization and mapping, contact modeling, grasping, and dexterous manipulation.
Prerequisites/Corequisites: Prerequisite/Corequisite: CSCI 4480.
When Offered: Spring term annually.
Cross Listed: Cross listed with CSCI 6490, ECSE 4490, ECSE 6490.
Credit Hours: 3
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CSCI 4500 - Distributed Computing Over The Internet
This course will enable students to understand and apply theoretical foundations of programming concurrent, distributed, and mobile computing systems, namely process calculi, actors, join calculus, and mobile ambients. In the practical part, students will compare communication and synchronization aspects in concurrent programming languages following these theoretical models. Students will also review current research on distributed computing over the Internet, on topics including but not limited to coordination, mobility, heterogeneity, security, fault tolerance, scalability, programmability, and verification. Students cannot receive credit for both CSCI 4500 and CSCI 6500.
Prerequisites/Corequisites: Prerequisites: CSCI 4430 and either CSCI 4210 or CSCI 4220 (or equivalent) or permission of instructor.
When Offered: Spring term annually.
Cross Listed: CSCI 6500.
Credit Hours: 4
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CSCI 4510 - Distributed Systems and Algorithms
This course explores the principles of distributed systems, emphasizing fundamental issues underlying the design of such systems: communication, coordination, synchronization, and fault-tolerance. Key algorithms and theoretical results will be studied and students will explore how these foundations play out in modern systems and applications.
Prerequisites/Corequisites: Prerequisite: CSCI 4210.
When Offered: Fall term annually.
Cross Listed: CSCI 6510. Students cannot receive credit for both CSCI 4510 and CSCI 6510.
Credit Hours: 4
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CSCI 4520 - Game Development I
This class is a practical primer for anyone interested in a career in the rapidly evolving industry of video gaming. It is an intense, team-based, project-based course in which students will closely follow the actual game development cycle, with each team producing a complete PC game. Students cannot get credit for both this course and COGS 4520.
Prerequisites/Corequisites: Prerequisites: COGS 2520 or CSCI 2300.
When Offered: Fall term annually.
Credit Hours: 4
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CSCI 4550 - Interactive Visualization
Visualizing data is a key step in understanding many problems. This course is designed to introduce students to methods of visualizing many different types of data, such as images, three-dimensional surfaces, flow fields, and medical data. Both existing visualization software and program custom visualizations using C++ and OpenGL will be used. Course activities include discussion of recent and classic research papers, weekly homework assignments, in-class critiques of visualization artifacts, and a final project to explore creative uses of these techniques. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and CSCI 2600, or permission of instructor.
When Offered: Spring term even-numbered years.
Cross Listed: CSCI 6550. Students cannot receive credit for both CSCI 4550 and CSCI 6550.
Credit Hours: 4
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CSCI 4700 - Technical Writing and Communication in Computer Science
The course is intended to provide a computational perspective on one or more topics chosen from theory and algorithms; systems and software; artificial intelligence and data; or vision, graphics, robotics, and games. Students will read classic and recent research results in the field, write critical reviews of these publications, engage in in-class presentations and discussions, and/or write a publication-quality report on an innovative final project of their choice.
Prerequisites/Corequisites: Prerequisites: CSCI 2200 or CSCI 2300 or CSCI 2600, plus additional prerequisites that vary with topic.
When Offered: Fall or spring terms annually, depending on availability and interest of instructors.
Credit Hours: 4
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CSCI 4800 - Numerical Computing
A survey of numerical methods for scientific and engineering problems. Topics include numerical solution of linear and nonlinear algebraic equations, interpolation and least squares approximations, numerical integration and differentiation, eigenvalue problems, and an introduction to the numerical solution of ordinary differential equations. Emphasis is placed on efficient computational procedures including the use of library and student written procedures using high-level software such as MATLAB.
Prerequisites/Corequisites: Prerequisites: CSCI 1100 and MATH 2010 or ENGR 1100. Corequisite: MATH 2400.
When Offered: Fall and spring terms annually.
Cross Listed: Cross listed as MATH 4800. Students cannot obtain credit for both this course and MATH 4800.
Credit Hours: 4
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CSCI 4820 - Introduction to Numerical Methods for Differential Equations
Derivation, analysis, and use of computational procedures for solving differential equations. Topics covered include ordinary differential equations (both initial value and boundary value problems) and partial differential equations. Runge-Kutta and multistep methods for initial value problems. Finite difference methods for partial differential equations including techniques for heat conduction, wave propagation, and potential problems. Basic convergence and stability theory.
Prerequisites/Corequisites: Prerequisite: MATH 4800 or CSCI 4800.
When Offered: Spring term annually.
Cross Listed: Cross listed as MATH 4820.
Credit Hours: 4
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CSCI 4940 - Readings in Computer Science
Credit Hours: 1 to 4
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CSCI 4960 - Topics in Computer Science
Credit Hours: 1 to 4
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CSCI 6040 - Approximation Algorithms
Algorithms with provable guarantees on the quality of their solutions are a powerful way of dealing with intractable problems. This course covers fundamental techniques for designing approximation algorithms. Possible topics include: semi-definite and linear programming, inapproximability and the PCP theorem, randomized rounding, metrics and cuts, primal-dual methods, and online algorithms. Students cannot receive credit for both CSCI 4040 and CSCI 6040.
Prerequisites/Corequisites: Prerequisite: CSCI 4020 or permission of instructor.
When Offered: Fall term odd-numbered years.
Cross Listed: CSCI 4040.
Credit Hours: 4
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CSCI 6050 - Computability and Complexity
This course discusses modern concepts of computability and computational complexity theories. The Church-Turing thesis; variations of Turing Machines; Algorithms; Decidability; The Halting Problem; Reducibility; The Recursion Theorem; The Concept of Information; Time and Space Complexity; Intractability; NP-completeness and Cook’s theorem. Students cannot receive credit for both CSCI 4050 and CSCI 6050.
Prerequisites/Corequisites: Prerequisite: CSCI 2300 or equivalent.
When Offered: Fall term annually.
Cross Listed: CSCI 4050.
Credit Hours: 3
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CSCI 6100 - Machine Learning from Data
Introduction to the theory, algorithms, and applications of machine learning (supervised, reinforcement, and unsupervised) from data: What is learning? Is learning feasible? How can we do it? How can we do it well? The course offers a mix of theory, technique, and application with additional selected topics chosen from Pattern Recognition, Decision Trees, Neural Networks, RBF’s, Bayesian Learning, PAC Learning, Support Vector Machines, Gaussian processes, and Hidden Markov Models. Students cannot receive credit for both CSCI 4100 and CSCI 6100.
Prerequisites/Corequisites: Prerequisites: CSCI 2300; an advanced 4000-level algorithms-based CSCI or MATH course; familiarity with probability, linear algebra, and calculus.
When Offered: Fall term annually.
Cross Listed: CSCI 4100.
Credit Hours: 4
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CSCI 6110 - Computational Social Processes
Introduction to the computational and algorithmic aspects of social processes. Topics covered will be selected to illustrate the diverse challenges in algorithmic social process analysis: social networks and their dynamics; information flow; hidden networks. Algorithms involving social and selfish agents, social choice theory, voting, and auctions. Ranking actors in networks, recommendation systems, peer-review, and aggregation of rankings/reviews. Students cannot receive credit for both CSCI 4110 and CSCI 6110.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and an advanced 4000-level algorithms-based CSCI or MATH course.
When Offered: Fall term even-numbered years, upon availability of instructor.
Cross Listed: CSCI 4110.
Credit Hours: 4
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CSCI 6120 - Computational Finance
Introduction to the computational and mathematical techniques for practical financial applications. The course will emphasize the algorithmic side of finance. Topics will be selected from pricing (options and derivatives), trading, risk-evaluation, selfish agents, sequential decisions, and portfolio optimization. Examples of the mathematical and algorithmic techniques covered are martingale measures, risk-neutral pricing and Monte Carlo, dynamic programing, and stochastic processes. Students cannot receive credit for both CSCI 4120 and CSCI 6120.
Prerequisites/Corequisites: Prerequisites: CSCI 2300; an advanced 4000-level algorithms-based CSCI or MATH course; familiarity with probability, linear algebra, and calculus.
When Offered: Fall term even-numbered years, upon availability of instructor.
Cross Listed: CSCI 4120.
Credit Hours: 4
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CSCI 6130 - Natural Language Processing
This course introduces state-of-the-art Natural Language Processing (NLP) methods, covering major popular research topics via the most-cited and up-to-date papers for each topic, as well as other resources. This course also covers machine learning methods for NLP. Students implement some of these methods and apply machine learning toolkits to solve a variety of problems. Assignments incorporate linguistics, mathematics, and careful thinking. Students cannot receive credit for both CSCI 4130 and CSCI 6130.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and MATH 2010.
When Offered: Fall term annually.
Cross Listed: CSCI 4130.
Credit Hours: 4
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CSCI 6140 - Computer Operating Systems
Topics include analysis of multiprogramming systems, virtual memory, computer system performance, and queuing theory. The course also discusses tools for synchronization of parallel programs and algorithms for mutual exclusion. Students cannot receive credit for both CSCI 4210 and CSCI 6140.
Prerequisites/Corequisites: Prerequisite: CSCI 2300 and either CSCI 2500 or ECSE 2660.
When Offered: Spring term annually.
Cross Listed: CSCI 4210.
Credit Hours: 4
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CSCI 6210 - Design and Analysis of Algorithms
Theoretical and empirical analysis of algorithms; tools for on-line monitoring of the algorithm’s performance. Advanced algorithms for polynomial problems; randomized heuristic and approximate algorithms. Problems include computation in discrete mathematics, number theory, linear algebra, graph theory, numerical and symbolic computing.
Prerequisites/Corequisites: Prerequisite: CSCI 4020 or equivalent.
When Offered: Spring term annually.
Credit Hours: 3
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CSCI 6220 - Randomized Algorithms
State-of-the-art in contemporary algorithm design, randomized algorithms are algorithms that use randomness as part of their functioning. They are typically simple, often easy to analyze, and work well in practice. They have numerous applications in many fields of computer science and mathematics. Randomized algorithms represent an active and vibrant research area with many exciting new results contributed every year. Students cannot receive credit for both CSCI 4030 and CSCI 6220.
Prerequisites/Corequisites: Prerequisite: CSCI 4020 or equivalent.
When Offered: Fall term annually.
Credit Hours: 4
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CSCI 6230 - Cryptography and Network Security I
A self-contained course that includes topics from number theory, basic cryptography, and protocol security. This is a hybrid course with sufficient depth in both theory and hands-on experience with network protocols. Topics include: Classical Cryptography, Block Ciphers (DES, AES), Information Theoretical Cryptography, Randomness, RNG and Stream Ciphers, Hash and MAC Algorithms, Public-Key Cryptography, Elliptic Curve Cryptography, Digital Signatures and Identification, Internet Attacks, Web Security, SSL and PGP. Students cannot receive credit for both CSCI 4230 and CSCI 6230.
Prerequisites/Corequisites: Prerequisites: CSCI 2300; also desirable is CSCI 4210 and CSCI 4220.
When Offered: Fall term annually.
Cross Listed: CSCI 4230.
Credit Hours: 4
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CSCI 6240 - Cryptography and Network Security II
A course covering advanced security topics with depth both in theory and hands-on exercises. Topics include: Probabilistic Encryption, Deniable Cryptography, Hardcore Predicates, All-or-Nothing Encryption, Secret Sharing, Subliminal/Covert Channels, Mental Poker, Goldwasser-Micali and Blum-Goldwasser Cryptosystems, Paillier PKC and Homomorphism, Elliptic Curve Cryptography, and Blind Signatures and E-cash. Students cannot receive credit for both CSCI 4240 and CSCI 6240.
Prerequisites/Corequisites: Prerequisites: CSCI 4230/6230; ECSE 4670 or CSCI 4220 or permission of instructor; also desirable is CSCI 4210.
When Offered: Spring term annually.
Cross Listed: CSCI 4240.
Credit Hours: 4
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CSCI 6250 - Frontiers of Network Science
This course will offer an introduction to network science and a review of current research in this area. Classes will interchangeably present chapters from the textbook and related current research. The emphasis will be on the mathematical background of network science: graphs and networks; random networks and various types of scale-free networks; network properties such as assortativity, mobility, robustness, social networks, and communities; and dynamics of spreading in networks. Students cannot receive credit for both CSCI 4250 and CSCI 6250.
Prerequisites/Corequisites: Prerequisites: CSCI 2300; a 4000-level algorithms-based CSCI course (e.g., 4020, 4050, 4260, 4800) or MATH course (e.g., 4100, 4150, 4200, 4210, 4800) course; familiarity with probability, linear algebra, and calculus; or permission of the instructor.
When Offered: Fall term odd-numbered years.
Cross Listed: CSCI 4250.
Credit Hours: 4
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CSCI 6270 - Computational Vision
The goal of this course is to introduce students to the problems, challenges, and applications of computer vision from a computational perspective. Topics include camera modeling and image formation, feature extraction, object and face recognition, image mosaic construction, stereo and three-dimensional imaging, motion, and tracking. Machine learning methods, including deep convolutional neural networks, will be studied and applied throughout the course. Students cannot receive credit for both CSCI 4270 and CSCI 6270.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and MATH 2010 or permission of instructor.
When Offered: Fall term odd-numbered years.
Cross Listed: CSCI 4270.
Credit Hours: 4
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CSCI 6340 - Ontologies
This course provides an introduction to ontologies, their uses, and an overview of their application in semantically enabled systems. Ontologies encode term meanings and are used to improve communication and enable computer programs to function more effectively. Class participants learn how to use ontologies in web-based applications and evaluate ontologies for reuse. Participants read relevant papers, learn how to critically review ontology papers and ontologies, and participate in group project(s) designing, using, and evaluating ontologies. Students cannot receive credit for both CSCI 4340 and CSCI 6340.
Prerequisites/Corequisites: Prerequisite: CSCI 2300.
When Offered: Spring term annually.
Cross Listed: CSCI 4340.
Credit Hours: 4
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CSCI 6350 - Data Science
Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity, and heterogeneity of data being made available over the Internet. It combines aspects of data management, library science, computer science, and physical science. It is changing the way all of these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught.
Prerequisites/Corequisites: Data Structures (CSCI 1200), Database Systems (CSCI 4380) preferred.
When Offered: Fall term annually.
Cross Listed: Cross listed as ITWS 4350/6350, CSCI 4350 and ERTH 4350/6350. Students can obtain credit for only one of these courses.
Credit Hours: 3
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CSCI 6360 - Parallel Computing
A survey of fundamental issues in design of efficient programs for parallel computers. The topics discussed include models of parallel machines and programs, efficiency of parallel algorithms, programming styles for shared memory, message passing, data parallelism, and using MPI in scientific parallel programs. Parallel programming project required. Students cannot receive credit for both CSCI 4320 and CSCI 6360.
Prerequisites/Corequisites: Prerequisite: CSCI 4210 or equivalent.
When Offered: Spring term annually.
Cross Listed: CSCI 4320.
Credit Hours: 4
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CSCI 6370 - Data and Society
Data and Society provides a broad overview of how society is leveraging and responding to the social, organizational, policy, and technical opportunities and challenges of a data-driven world. Course themes focus on various aspects of the data ecosystem, data and innovation, and data and the broader community. Assignments build writing, presentation, and critical thinking and assessment skills, all of which are important for professional success. This is a communication-intensive course.
Prerequisites/Corequisites: CSCI 4350/6350 or ITWS 4350/6350 or permission of instructor.
When Offered: Spring term annually.
Cross Listed: CSCI 4370. Students cannot receive credit for both CSCI 4370 and CSCI 6370.
Credit Hours: 4
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CSCI 6390 - Data Mining
This course will provide an introductory survey of the main topics in data mining and knowledge discovery in databases (KDD), including: classification, clustering, association rules, sequence mining, similarity search, deviation detection, and so on. Emphasis will be on the algorithmic and system issues in KDD, as well as on applications such as Web mining, multimedia mining, bioinformatics, geographical information systems, etc. Students cannot receive credit for both CSCI 4390 and CSCI 6390.
Prerequisites/Corequisites: Prerequisites: CSCI 2300.
When Offered: Fall term annually.
Cross Listed: CSCI 4390.
Credit Hours: 4
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CSCI 6400 - Xinformatics
Informatics covers a broad range of disciplines addressing challenges in the explosion of data and information resources. Xinformatics provides commonality for implementations in specific disciplines, e.g. X=astro, geo. Informatics’ theoretical bases are information and computer science, cognitive science, social science, library science, aggregating these studies and adding the practice of information processing, and the engineering of information systems. This course grounds the material that students will learn in discipline areas by coursework and project assignments.
Prerequisites/Corequisites: CSCI 1200 and Data Science (CSCI/ERTH/ITWS 496x/696x).
When Offered: Spring term annually.
Cross Listed: Cross listed as ITWS 4400/6400, CSCI 4400 and ERTH 4400/6400. Students can only obtain credit for one of these courses.
Credit Hours: 3
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CSCI 6430 - Programming Languages
This course is a study of the important concepts found in current programming languages. Topics include language processing (lexical analysis, parsing, type-checking, interpretation and compilation, run-time environment), the role of abstraction (data abstraction and control abstraction), programming paradigms (procedural, functional, object-oriented, logic-oriented, generic), and formal language definition. Students cannot receive credit for both CSCI 4430 and CSCI 6430.
Prerequisites/Corequisites: Prerequisite: CSCI 2300 and CSCI 2600.
When Offered: Fall term annually.
Cross Listed: CSCI 4430.
Credit Hours: 3
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CSCI 6450 - Principles of Program Analysis
The goal of this course is to introduce students to program analysis and its many applications in software engineering, particularly in improving software quality and software productivity. Concretely, students who successfully complete this course should be able to: (1) understand and apply program analysis techniques, such as dataflow analysis and type-based analysis; (2) implement program analysis; (3) understand and apply software testing techniques, such as black-box testing and white-box testing; and (4) understand and apply refactoring techniques.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and CSCI 2600.
When Offered: Spring term even-numbered years.
Cross Listed: CSCI 4450. Students cannot receive credit for both CSCI 4450 and CSCI 6450.
Credit Hours: 4
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CSCI 6490 - Robotics II
This course introduces methods that leverage the basic analysis techniques learned in Robotics I to develop numerical and algorithmic techniques needed to endow robots with the “intelligence” to devise strategies to solve problems they will encounter. Once these abilities are sufficiently well developed, robots will become safe and autonomous, thus paving the way for pervasive personal robots. Topics include: configuration space representation, cell decomposition, roadmap methods, rapidly-exploring random trees, simultaneous localization and mapping, contact modeling, grasping, and dexterous manipulation.
Prerequisites/Corequisites: Prerequisite: CSCI 4480.
When Offered: Spring term annually.
Cross Listed: Cross listed with ECSE 6490, CSCI 4490, ECSE 4490.
Credit Hours: 3
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CSCI 6500 - Distributed Computing Over The Internet
This course will enable students to understand and apply theoretical foundations of programming concurrent, distributed, and mobile computing systems, namely process calculi, actors, join calculus, and mobile ambients. In the practical part, students will compare communication and synchronization aspects in concurrent programming languages following these theoretical models. Students will also review current research on distributed computing over the Internet, on topics including but not limited to coordination, mobility, heterogeneity, security, fault tolerance, scalability, programmability, and verification. Students cannot receive credit for both CSCI 4500 and CSCI 6500.
Prerequisites/Corequisites: Prerequisites: CSCI 4430 and either CSCI 4210 or CSCI 4220 (or equivalent) or permission of instructor.
When Offered: Spring term annually.
Cross Listed: CSCI 4500.
Credit Hours: 4
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CSCI 6510 - Distributed Systems and Algorithms
This course explores the principles of distributed systems, emphasizing fundamental issues underlying the design of such systems: communication, coordination, synchronization, and fault-tolerance. Key algorithms and theoretical results will be studied and students will explore how these foundations play out in modern systems and applications.
Prerequisites/Corequisites: Prerequisite: CSCI 4210.
When Offered: Fall term annually.
Cross Listed: CSCI 4510. Students cannot receive credit for both CSCI 4510 and CSCI 6510.
Credit Hours: 4
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CSCI 6530 - Advanced Computer Graphics
In this course, there will be a survey of classic papers and current research in computer graphics. Topics include: advanced ray tracing, global illumination, photon mapping, subsurface scattering, mesh generation and simplification, subdivision surfaces, volumetric modeling, procedural modeling and texturing, weathering, physical simulation, appearance models. Course activities include programming assignments, oral presentations, and a term project. Students cannot receive credit for both CSCI 4530 and CSCI 6530. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and CSCI 2600; previous coursework or experience in computer graphics such as ECSE 4750 or computational geometry is recommended.
When Offered: Spring term annually.
Cross Listed: CSCI 4530.
Credit Hours: 4
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CSCI 6550 - Interactive Visualization
Visualizing data is a key step in understanding many problems. This course is designed to introduce students to methods of visualizing many different types of data, such as images, three-dimensional surfaces, flow fields, and medical data. Both existing visualization software and program custom visualizations using C++ and OpenGL will be used. Course activities include discussion of recent and classic research papers, weekly homework assignments, in-class critiques of visualization artifacts, and a final project to explore creative uses of these techniques. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisites: CSCI 2300 and CSCI 2600, or permission of instructor.
When Offered: Spring term even-numbered years.
Cross Listed: CSCI 4550. Students cannot receive credit for both CSCI 4550 and CSCI 6550.
Credit Hours: 4
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CSCI 6800 - Computational Linear Algebra
Gaussian elimination, special linear systems (such as positive definite, banded, or sparse), introduction to parallel computing, iterative methods for linear systems (such as conjugate gradient and preconditioning), QR factorization and least squares problems, and eigenvalue problems.
Prerequisites/Corequisites: Prerequisite: MATH 4800 or CSCI 4800 or permission of instructor.
When Offered: Fall term even-numbered years.
Cross Listed: Cross listed as MATH 6800. Students cannot obtain credit for both this course and MATH 6800.
Credit Hours: 4
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CSCI 6820 - Numerical Solution of Ordinary Differential Equations
Numerical methods and analysis for ODEs with applications from mechanics, optics, and chaotic dynamics. Numerical methods for dynamic systems include Runge-Kutta, multistep and extrapolation techniques, methods for conservative and Hamiltonian systems, methods for stiff differential equations and for differential-algebraic systems. Methods for boundary value problems include shooting and orthogonalization, finite difference and collocation techniques, and special methods for problems with boundary or shock layers.
Prerequisites/Corequisites: Prerequisite: MATH 4800 or CSCI 4800 or permission of instructor.
When Offered: Spring term odd-numbered years.
Cross Listed: Cross listed as MATH 6820. Students cannot obtain credit for both this course and MATH 6820.
Credit Hours: 4
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CSCI 6840 - Numerical Solution of Partial Differential Equations
Numerical methods and analysis for linear and nonlinear PDEs with applications from heat conduction, wave propagation, solid and fluid mechanics, and other areas. Basic concepts of stability and convergence (Lax equivalence theorem, CFL condition, energy methods). Methods for parabolic problems (finite differences, method of lines, ADI, operator splitting), methods for hyperbolic problems (vector systems and characteristics, dissipation and dispersion, shocks capturing and tracking schemes), methods for elliptic problems (finite difference and finite volume methods).
Prerequisites/Corequisites: Prerequisite: MATH 4800 or CSCI 4800 or permission of instructor.
When Offered: Fall term odd-numbered years.
Cross Listed: Cross listed as MATH 6840. Students cannot obtain credit for both this course and MATH 6840.
Credit Hours: 4
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CSCI 6860 - Finite Element Analysis
Galerkin’s method and extremal principles, finite element approximations (Lagrange, hierarchical and 3-D approximations, interpolation errors), mesh generation and assembly, adaptivity (h-, p-, hp-refinement). Error analysis and convergence rates. Perturbations resulting from boundary approximation, numerical integration, etc. Time dependent problems including parabolic and hyperbolic PDEs. Applications will be selected from several areas including heat conduction, wave propagation, potential theory, and solid and fluid mechanics.
Prerequisites/Corequisites: Prerequisite: MATH 4800 or CSCI 4800 or permission of instructor.
When Offered: Spring term even-numbered years.
Cross Listed: Cross listed as MATH 6860. Students cannot obtain credit for both this course and MATH 6860.
Credit Hours: 4
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CSCI 6900 - Computer Science Seminar
Presentation of current developments in computer science. Reports by students.
Credit Hours: 1
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CSCI 6940 - Readings in Computer Science
Credit Hours: 1 to 3
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CSCI 6960 - Topics in Computer Science
Credit Hours: 1 to 3
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CSCI 6970 - Professional Project
Active participation in a semester-long project, under the supervision of a faculty adviser. A Professional Project often serves as a culminating experience for a Professional Master’s program but, with departmental or school approval, can be used to fulfill other program requirements. With approval, students may register for more than one Professional Project. Professional Projects must result in documentation established by each department or school, but are not submitted to the Office of Graduate Education and are not archived in the library. Grades of A, B, C, or F are assigned by the faculty adviser at the end of the semester. If not completed on time, a formal Incomplete grade may be assigned by the faculty adviser, listing the work remaining to be completed and the time limit for completing this work.
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CSCI 6980 - Master’s Project
Active participation in a master’s-level project under the supervision of a faculty adviser, leading to a master’s project report. Grades of IP are assigned until the master’s project has been approved by the faculty adviser. If recommended by the adviser, the master’s project may be accepted by the Office of Graduate Education to be archived in the Library. Grades will then be listed as S.
Credit Hours: 1 to 9
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CSCI 6990 - Master’s Thesis
Active participation in research, under the supervision of a faculty adviser, leading to a master’s thesis. Grades of S or U are assigned by the adviser each term to reflect the student’s research progress for the given semester. Once the thesis has been presentend, approved by the adviser, and accepted by the Office of Graduate Education, it will be archived in a standard format in the library.
Credit Hours: 1 to 9
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CSCI 9990 - Dissertation
Active participation in research, under the supervision of a faculty adviser, leading to a doctoral dissertation. Grades of IP are assigned until the dissertation has been publicly defended, approved by the doctoral committee, and accepted by the Office of Graduate Education to be archived in a standard format in the library. Grades will then be listed as S.
Credit Hours: Variable
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ECON 1200 - Introductory Economics
Every society faces the question of choosing how to use its natural and human resources to produce goods and services and how to distribute these resources among its people. This course studies how these choices are made in markets. It also explains the determinants of total output, employment, and inflation. Attention may also be given to special topics such as the environment, trade, and population.
When Offered: Fall and spring terms annually.
Credit Hours: 4
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ECON 2010 - Intermediate Microeconomic Theory
Applies the microeconomic theory of the firm to price, cost, and output decisions of business enterprises under different market structures. Regression analysis of demand and cost, linear programming of production and simulation analysis of risk, and capital budgeting are also presented.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Fall and spring terms annually.
Credit Hours: 4
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ECON 2020 - Intermediate Macroeconomic Theory
Attention is directed primarily to variations in the aggregate volume of output, income, and employment. Cyclical fluctuations and long-term economic trends are examined and the interrelations of business and government policies are analyzed. The applicability of economic theory to the problems of business forecasting is discussed.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Fall and spring terms annually.
Credit Hours: 4
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ECON 2940 - Readings in Economics
Credit Hours: 3 or 4
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ECON 2960 - Topics in Economics
Selected topics in economics designed to acquaint students with modern economic problems and analysis in special areas beyond the introductory level.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or equivalent.
Credit Hours: 4
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ECON 4110 - Economic Analysis of Technological Change
An examination of the economic considerations that influence the creation and assimilation of new products and processes, and of the impact of technological change on the structures and evolution of the American economy and environment. Topics include productivity growth, the organization and management of industrial research and development, the interaction between technological change and industrial structure, diffusion of innovations, and technological unemployment. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4120 - Mathematical Methods in Economics
Application of mathematical techniques to economic modeling and analysis. Construction of models to describe aspects of the economy and to analyze potential policies. Solution methods for issues including optimal choice with and without constraints, equilibria among multiple actors, marginal effects of policies, and dynamic economic models. Some mathematical maturity is assumed, and mathematical skills are taught throughout the course.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Fall term annually.
Cross Listed: Cross listed with ECON 6120; students cannot obtain credit for both courses.
Credit Hours: 4
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ECON 4130 - Money and Banking
Financial institutions, especially commercial banking and the Federal Reserve System, are considered from three perspectives: their monetary roles; trends in the economic, organizational, and technological aspects of their operations; and their other economic roles-a critical view. Also, the role of money in macroeconomic theory is considered along with the role of monetary policies in relation to the problems of inflation and unemployment.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Fall and spring terms annually.
Credit Hours: 4
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ECON 4140 - Structure of Industry: Competition, Innovation, Entrepreneurship, Policy
Acquaints students with the structural characteristics and philosophical foundations of enterprise and industry. Several important industries are considered from the viewpoint of market structure, conduct, and performance. Such concepts as the corporation, entrepreneurial outcomes, technological innovation, private property, and public policy toward business are examined to orient the student to contemporary industrial activity.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Cross Listed: Cross listed with ECON 6140; students cannot obtain credit for both courses.
Credit Hours: 4
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ECON 4150 - Economics of Government Regulation
Can government intervention improve the performance of private markets and if so, when and how? How is regulatory policy actually made, and what effects has it had? These questions are applied to the experience in the U.S. and elsewhere with telecommunications, electricity, transportation, financial services, job safety, and environmental regulation.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4160 - Public Finance
Emphasis is placed on the analysis of efficient resource use in the public sector at the federal level. Expenditure theory, tax incidence, and income distribution policies are discussed. The effects of personal income, corporation, sales, payroll, and property taxes on resource allocation, equity, and growth are considered.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4180 - Development of Economic Thought
A critical examination in which comparisons are made and contrasts emphasized between different schools of economic thinking such as classicism, marginalism, socialism, institutionalism, neoclassicism, and Keynesianism. Special attention is given to historical theories and attitudes of economists toward technological change and its impact on human welfare.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4190 - International Economics and Globalization
This course investigates the significance of economic globalization, covering the following topics: international trade and financial flows, technological innovation and intellectual property, technology transfer, national government and transnational corporations, natural resources, health and the environment, impacts on selected industries and countries, and roles of the world trade organization and international monetary fund. The major controversies surrounding globalization are identified, and alternative arguments are evaluated based on available evidence.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4210 - Cost-Benefit Analysis
Addresses the identification and measurement of the economic gains and losses to different sectors of the economy resulting from public projects and policies. Among the projects studied are those in the area of transportation, energy, environment, and urban development. Also considered is the evaluation of the effects of government on business, as for example, consumer product and workplace safety regulation.
Prerequisites/Corequisites: Prerequisite: ECON 2010.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4230 - Environmental Economics
Develops a critical understanding of environmental issues and policy from an interdisciplinary economics perspective. Covers the economics of environmental quality including the links between the economy and the environment, the causes of environmental problems, evaluation of environmental projects and policies, and policies to address environmental issues with an emphasis on efficiency, equity, and sustainability, and the international dimensions of environmental issues.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor. ECON 2010 recommended.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4240 - Natural Resource Economics
Addresses the allocation of natural resources through applied study of fisheries, forestry, oil, minerals, water, and biodiversity resources. Mathematical analysis will be done using Microsoft Excel with Solver. Social and policy dynamics of allocation decisions will be explored through case studies. Field trips will address ecological and physical aspects of resource management. The intent is to develop a balanced perspective and tools to address resource management decisions across their diverse economic, social, and environmental dimensions. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4250 - Economy, Technology, & Sustainability
This course explores the relationships between the economy and the material world. It identifies the most critical challenges to sustainable economic development on local to global scales and ways of addressing them. The course examines options surrounding material and energy flows, technological alternatives, livelihoods, consumption behavior, public policy, civil society institutions, and social movements as avenues for meeting the major challenges to sustainability.
Prerequisites/Corequisites: Prerequisites: ECON 1200 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 4
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ECON 4260 - Environmental and Resource Economics
Introduces students to the basic analytical approaches to environmental issues and natural resource use. Emphasis is on economic valuation and public policy. Covers traditional approaches based on assumptions of economic rationality and market efficiency as well as current approaches from the fields of environmental science behavioral economics. Emphasis is on active student participation and examination of current environmental controversies.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or equivalent or permission of instructor.
When Offered: Upon availability of instructor.
Cross Listed: Cross listed with ECON 6260; students cannot received credit for both.
Credit Hours: 4
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ECON 4570 - Econometrics
This course is an introduction to econometric data analysis. The statistical methods covered enable analysis of relationships between variables in data, with special attention to indentification of true casual effects. Topics covered include linear and simple nonlinear regression models, internal and external validity, methods for panel data and binary dependent variables, instrumental variable methods, use of experiemntal and quasi-experimental data, and basic time series methods. The course included hands-on data analysis and report writing.
Prerequisites/Corequisites: Prerequisites: MATH 2010 or equivalent, ECON 2010 or equivalent, and approved statistics course or permission of instructor.
When Offered: Fall and spring terms annually.
Cross Listed: Cross listed with ECON 6560; students cannot obtain credit for both courses.
Credit Hours: 4
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ECON 4900 - Seminar in Economics
Discussion and analysis of selected topics in economic theory and of current economic issues. This is a communication-intensive course.
Prerequisites/Corequisites: Prerequisities: ECON 4570.
When Offered: Fall and spring terms annually.
Credit Hours: 2 to 4
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ECON 4940 - Readings in Economics
Credit Hours: 3 to 4
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ECON 4960 - Topics in Economics
Selected topics in economic analysis and problems to meet the special needs of upper-division students in various curricula throughout the Institute. This allows students to pursue more in-depth work in their areas of study.
Prerequisites/Corequisites: Prerequisites: ECON 1200 and permission of instructor.
Credit Hours: 4
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ECON 6120 - Advanced Mathematical Methods in Economics
Mathematical techniques applied to theoretical models in economics. Reviews and introduces core mathematical topics at the graduate economics level, applied to topics such as optimal behaviors of economics agents, equilibria among multiple interacting agents, economics growth processes and inter-temporal decision making, decision making in stochastic enviroments, and techniques to develop and work with economic models. Assumes thorough knowledge of calculus and some familiarity with linear algebra and probability theory.
When Offered: Fall term annually.
Cross Listed: Cross listed with ECON 4120; students cannot obtain credit for both courses.
Credit Hours: 3
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ECON 6140 - Advanced Structure of Industry
An advanced analysis of current problems confronting major American industries, regulated and unregulated. Recent changes in growth patterns, market structures, and pricing policies are examined. Considerable emphasis is placed on emerging trends in technology and public policy, which are likely to affect significantly the future of these industries.
Prerequisites/Corequisites: Prerequisites: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Cross Listed: Cross listed with ECON 4140; students cannot obtain credit for both courses.
Credit Hours: 3
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ECON 6150 - Advanced Economics of Government Regulation
Can government intervention improve the performance of private markets and if so, when and how? How is regulatory policy actually made, and what effects has it had? These questions are applied to the experience in the U.S. and elsewhere with telecommunications, electricity, transportation, financial services, job safety, health, and environmental regulation.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6160 - Advanced Public Finance
Emphasis is placed on the analysis of efficient resource use in the public sector at the federal level. Expenditure theory and tax incidence are discussed. The effects of personal income, corporation, sales, payroll, and property taxes on resource allocation, equity, growth, and technological change are considered.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6190 - Advanced International Economics and Globalization
This course investigates the significance of economic globalization, covering the following topics: international trade and financial flows, technological innovation and intellectual property, technology transfer, national governments and transnational corporations, natural resources, health and the environment, impacts on selected industries and countries, and roles of the World Trade Organization and International Monetary Fund. The major controversies surrounding globalization are identified, and alternative arguments are evaluated based on available evidence.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6210 - Advanced Cost-Benefit Analysis
The techniques necessary to appraise the economic desirability and private-sector impact of various public projects and policies are studied. Concepts such as discounting, capital rationing, project selection, shadow pricing, risk assessment, unpriced goods, and economic surplus are developed. Among the topics from which illustrative case studies are drawn are urban and transport planning, energy, water resources, government regulation, and the environment. Suitable for graduate students in professional programs.
Prerequisites/Corequisites: Prerequisite: ECON 6490 or ECON 2010.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6230 - Advanced Environmental Economics
Develops a critical understanding of environmental issues and policy and the environmental economics literature. Covers the economics of environmental quality including the links between the economy and the environment, the causes of environmental problems, evaluation of environmental projects and policies, and policies to address environmental issues with an emphasis on efficiency, equity, and sustainability, and the international dimensions of environmental issues.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or permission of instructor.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6240 - Advanced Natural Resource Economics
Addresses the allocation of natural resources through applied study of fisheries, forestry, oil, minerals, water, and biodiversity resources. Mathematical analysis will be done using Microsoft Excel with Solver. Social and policy dynamics of allocation decisions will be explored through case studies. Field trips will address ecological and physical aspects of resource management. The intent is to develop a balanced perspective and tools to address resource management decisions across their diverse economic, social, and environmental dimensions.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6250 - Advanced Economy, Technology, and Sustainability
This course explores the relationships between the economy and the material world. It identifies the most critical challenges to sustainable economic development on local to global scales and ways of addressing them. The course examines options surrounding material and energy flows, technological alternatives, livelihoods, consumption behavior, public policy, civil society institutions, and social movements as avenues for meeting the major challenges to sustainability.
Prerequisites/Corequisites: Prerequisite: ECON 1200 or permission of instructor; graduate student status.
When Offered: Upon availability of instructor.
Cross Listed: Cross listed with ECON 4250; students cannot obtain credit for both courses.
Credit Hours: 3
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ECON 6260 - Advanced Environmental and Resource Economics
Develops a critical understanding of environmental and natural resource issues and policy and the environmental and natural resource economics literature. Covers the economics of environmental quality and natural resources including the links between the economy and the environment, the causes of environmental problems, the economics of resource exploitation, environmental and resource project evaluation, and policies to address environmental and resource issues. Emphasizes efficiency, equity, sustainability, and international dimensions of the issues.
When Offered: Upon availability of instructor.
Cross Listed: Cross listed with ECON 4260; students cannot receive credit for both courses.
Credit Hours: 3
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ECON 6490 - Introduction to Economic Theory
The course examines the basic concepts and techniques of economic analysis and their applications to economics problems at the level of the firm, industry, and economy as a whole. Topics include theory of product and factor pricing, national income and employment theory, monetary and fiscal theories, economic growth and fluctuations.
When Offered: Upon availability of instructor.
Credit Hours: 3
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ECON 6550 - Advanced Microeconomic Analysis
The central propositions of contemporary economic analysis are set forth. Topics include interaction of firms and households; determination through the market of resource allocation, outputs, prices, and incomes; capital and interest; theories of general equilibrium; static and dynamic models.
Prerequisites/Corequisites: Prerequisite: ECON 2010 or ECON 6490 or permission of instructor.
When Offered: Fall term annually.
Credit Hours: 3
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ECON 6560 - Introduction to Econometrics
This course is an introduction to econometric data analysis. The statistical methods covered enable analysis of relationships between variables in data, with special attention to identification of true causal effects. Topics covered include linear and simple nonlinear regression models, internal and external validity, methods for panel data and binary dependent variables, instrumental variables methods, use of experimental and quasi-experimental data, and basic time series methods. The course includes hands-on data analysis and report writing.
Prerequisites/Corequisites: Prerequisite: MATH 2010 or equivalent, ECON 2010 or equivalent, and approved statistics course or permission of instructor.
When Offered: Fall and spring terms annually.
Cross Listed: Cross listed with ECON 4570; students cannot obtain credit for both courses.
Credit Hours: 3
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ECON 6570 - Advanced Econometrics
Application of statistical and mathematical techniques to analyze economic data. The formulation and interpretation of mathematical models that involve quantifiable economic relationships. The role of probability theory and statistical inference in the solution of model systems. Small-sample and asymptotic OLS regression, instrumental variables and GMM, multi-equation systems, panel data analysis, and maximum likelihood estimation including for binary, censored, and truncated dependent variables. Some mathematical facility is assumed.
When Offered: Spring term annually.
Credit Hours: 3
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