Courses

• CAS CS 520: Programming Languages
  Concepts of programming languages: data, storage, control, and definition structures; concurrent and distributed programming; functional and logic programming.
• CAS CS 530: Advanced Algorithms
  Studies the design and efficiency of algorithms in several areas of computer science. Topics are chosen from graph algorithms, sorting and searching, NP-complete problems, pattern matching, parallel algorithms, and dynamic programming.
• CAS CS 535: Complexity Theory
  Covers topics of current interest in the theory of computation chosen from computational models, games and hierarchies of problems, abstract complexity theory, informational complexity theory, time-space trade-offs, probabilistic computation, and recent work on particular combinatorial problems.
• CAS CS 538: Fundamentals of Cryptography
  Basic Algorithms to guarantee confidentiality and authenticity of data. Definitions and proofs of security for practical constructions. Topics include perfectly secure encryption, pseudorandom generators, RSA and Elgamal encryption, Diffie-Hellman key agreement, RSA signatures, secret sharing, block and stream ciphers.
• CAS CS 542: Machine Learning
  Introduction to modern machine learning concepts, techniques, and algorithms. Topics include regression, kernels, support vector machines, feature selection, boosting, clustering, hidden Markov models, and Bayesian networks. Programming assignments emphasize taking theory into practice, through applications on real-world data sets.
• CAS CS 548: Advanced Cryptography
  Continuation of CAS CS 538. Advanced techniques to preserve confidentiality and authenticity against active attacks, zero-knowledge proofs; Fiat-Shamir signature schemes; non-malleable public-key encryption; authenticated symmetric encryption; secure multiparty protocols for tasks ranging from Byzantine agreement to mental poker to threshold cryptography.
• CAS CS 552: Introduction to Operating Systems
  Examines process synchronization; I/O techniques, buffering, file systems; processor scheduling; memory management; virtual memory; job scheduling, resource allocation; system modeling; and performance measurement and evaluation.
• CAS CS 556: Advanced Computer Networks
  Strengthens understanding of networking issues and solutions. Relates fundamental concepts, requirements, and design tradeoffs to scheduling, congestion control, routing, traffic management, wireless access and mobility, and applications. Considers how networking may evolve to provide ubiquitous support for quality-of-service in heterogeneous environments.
• CAS CS 558: Computer Networks Security
  Introduces basic principles and techniques of building secure information systems. Covers network security, web security, privacy, and basic cryptographic tools (symmetric and public key cryptography, encryption, key exchange, hashing and signatures). Broader social, legal and political aspects of security addressed.
• CAS CS 562: Advanced Database Applications
  Research issues in the design and implementation of modern database systems. Spatial, temporal, and spatiotemporal index structures. Indexing methods for image and multimedia databases and data warehouses. New data analysis techniques for large databases, clustering and rule discovery for very large datasets.
• CAS CS 565: Data Mining
  Introduction to data mining concepts and techniques. Topics include association and correlation discovery, classification and clustering of large datasets, outlier detection. Emphasis on the algorithmic aspects as well as the application of mining in real-world problems.
• CAS CS 585: Image and Video Computing
  Introduction to images and video as multimedia data types and algorithms for image and video understanding based on color, shading, stereo, and motion. Topics include face recognition, human-computer interfaces, animal and vehicle tracking, and medical image analysis.
• CAS CS 591: Topics in Computer Science
  Various issues in computer science. Two topics are offered Fall 2015. Students may take one or both for credit. Section B1: E-Commerce. Inter-disciplinary perspectives on electronic commerce from seminal papers on theoretical foundations and empirical findings in computer science, information systems, marketing, and economics communities; specific fluency with big data; experimental methods; best practices in data collection, mining, analysis, and ethics. Section C1: Graph Theory for the Internet Age. Review of basic graph theory, definitions, key concepts, theorems, and algorithms. Introduces advanced concepts such as random graph theory and spectral graph theory. Investigates models and concepts that describe real-world networks, scale-free networks, preferential attachment, sparse and inhomogenous models, etc.
• CAS EC 101: Introductory Microeconomic Analysis
  The first semester of a standard two-semester sequence for those considering further work in management or economics. Coverage includes economics of households, business firms, and markets; consumer behavior and the demand for commodities; production, costs, and the supply of commodities; price determination; competition and monopoly; efficiency of resource allocation; governmental regulation; income distribution; and poverty. Carries social science divisional credit in CAS.
• CAS EC 102: Introductory Macroeconomic Analysis
  The second semester of a standard two-semester sequence for those considering further work in management or economics. National economic performance; the problems of recession, unemployment, and inflation; money creation, government spending, and taxation; economic policies for full employment and price stability; and international trade and payments. Carries social science divisional credit in CAS.
• CAS EC 201: Intermediate Microeconomic Analysis
  Determination of commodity prices and factor prices under the differing market conditions of competition and monopoly.
• CAS EC 202: Intermediate Macroeconomic Analysis
  Determination of aggregate income and employment. Analysis of fiscal and monetary policy. Inflation and incomes policy. Problems of the open economy.
• CAS EC 204: Empirical Economics 2
  Builds on the material in EC203, developing more complex statistical techniques and applications. This course covers similar material to that in CAS EC 304 but in a more applied fashion (students who desire a more mathematically intense introduction to econometrics should consider taking EC 304 rather than EC 204). Note that students may not receive credit for both EC 204 and EC 304. Either EC 204 or EC 304 may be counted as one of the three required electives in the economics minor.
• CAS EC 303: Empirical Economic Analysis 1
  Statistical techniques are presented and applied to a variety of economics problems. Extensive use of the statistical software package STATA. This is a more theoretically advanced version of CAS EC 203. Note that students may not receive credit for both CAS EC 203 and EC 303.
• CAS EC 304: Empirical Economic Analysis 2
  Builds on the material in CAS EC 303, developing more complex statistical techniques and applications. This is a more theoretically advanced version of CAS EC 204. Note that students may not get credit for both EC 204 and EC 304. Either EC 204 or EC 304 may be counted as one of the three required electives in the economics minor.

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