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COMPSCI 149S: Problem Solving Seminar
0.50 Credits
Duke University
Techniques for attacking, solving, and writing computer programs for challenging computational problems. Algorithmic and programming language tool kits. Course may be repeated. Consent of instructor required. Instructor: Astrachan
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COMPSCI 150: Introduction to Numerical Methods and Analysis
1.00 Credits
Duke University
Theory, algorithms, and software that concern numerical solution of linear equations, approximation and interpolation of functions, numerical solution of nonlinear equations, and numerical solution of ordinary differential equations. Prerequisite: Computer Science 6; Mathematics 31; 32; 104 or 111. Instructor: Rose or Sun
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COMPSCI 150 - Introduction to Numerical Methods and Analysis
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COMPSCI 150S: Introduction to Numerical Methods and Analysis
1.00 Credits
Duke University
Seminar version of Computer Science 150
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COMPSCI 160: Introduction to Computational Genomics
1.00 Credits
Duke University
A computational perspective on the analysis of genomic and genome-scale information. Focus on exploration and analysis of large genomic sequences, but also attention to issues in structural and functional genomics. Topics include genome sequence assembly, local and global alignment, gene and motif finding, protein threading and folding, and the clustering and classification of genes and tissues using gene expression data. Students to learn computational approaches to genomics as well as to develop practical experience with handling, analyzing, and visualizing information at a genome-scale. Instructor: Hartemink
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COMPSCI 170: Introduction to Artificial Intelligence
1.00 Credits
Duke University
Algorithms and representations used in artificial intelligence. Introduction and implementation of algorithms for search, planning, decision, theory, logic, Bayesian networks, robotics and machine learning. Prerequisite: Computer Science 100. Instructor: Parr
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COMPSCI 173: Computational Microeconomics
1.00 Credits
Duke University
Use of computational techniques to operationalize basic concepts from economics. Expressive marketplaces: combinatorial auctions and exchanges, winner determination problem. Game theory: normal and extensive-form games, equilibrium notions, computing equilibria. Mechanism design: auction theory, automated mechanism design. Prerequisites: 100-level Statistics and 100-level Mathematics or consent of instructor. Instructor: Conitzer
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COMPSCI 173 - Computational Microeconomics
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COMPSCI 181S: Computer Science Seminar
1.00 Credits
Duke University
In-depth exploration of specific areas in computer science. The methods of critical inquiry and scholarly research reinforced with regular written analysis, seminar-style presentations and collaborative research projects. Prerequisites: Computer Science 100 and 104. Instructor: Staff
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COMPSCI 181S - Computer Science Seminar
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COMPSCI 182S: Technical and Social Analysis of Information and the Internet
1.00 Credits
Duke University
Technical version of Computer Science 82S. Requires a significant technical project. The development of technical and social standards governing the Internet and information technology in general. The role of software as it relates to law, patents, intellectual property, and IETF (Internet Engineering Task Force) standards. Written analysis of issues from a technical perspective with an emphasis on the role of software and on how standards relate to social and ethical issues. Meets as a seminar with an additional weekly meeting to accommodate guest lectures. Not open to students who have taken Computer Science 82S. Prerequisites: Computer Science 108 and recommended Computer Science 116. Instructor: Astrachan and Forbes
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COMPSCI 189S: CompSci Majors - Project-based Robotics Course with Service Learning
0.50 Credits
Duke University
Project-based robotics course linked with community service. Introduction and implementation of algorithms for navigation, map building, and object recognition. Representing uncertainty in robot motion and sensing. Mentoring students in local schools. After taking this course, students should be able to reason about the core algorithms and challenges present in the field of autonomous mobile robotics; and effectively convey and formulate mobile robotics curricula for middle or high school students. Prerequisite: CompSci 100 or equivalent programming experience. Instructor: Forbes.
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COMPSCI 189S - CompSci Majors - Project-based Robotics Course with Service Learning
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COMPSCI 18S: Introduction to Problem Solving
0.50 Credits
Duke University
Techniques for solving computational problems in groups and individually. Topics vary every semester the course is offered. Course may be repeated once. Consent of instructor required. Co-requisite: Enrollment in Computer Science 4 or Computer Science 6. Instructor: Rodger
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COMPSCI 18S - Introduction to Problem Solving
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