News; Give to Tulane; Medical Center; Contact Us; Website Feedback CMPS 1500  Intro to Computer Science I  (4) Â. Computational tools are a critical part of our everyday lives. This course is an introduction to logic and its applications in computer science. This course covers the fundamental concepts in distributed computing. Future doctors don't have to major in science, so don't be afraid to choose a nontraditional degree path. This course studies the mathematics underlying computer security, including both public key and symmetric key cryptography, crypto-protocols and information flow. Applications to various areas are also featured in the course. Special topics in Computer Science. In addition, several examples of applications will be described. CMPS 6260  Advanced Algorithms  (3) Â. In this course, we will focus on the myriad of algorithms for analyzing numerous aspects of protein structure and protein-protein interactions. CMPS 3350  Intro to Computer Graphics  (3) Â. 6823 St. Charles Avenue New Orleans, LA 70118 504-865-5000. CMPS 4910  Independent Study  (1-3) Â. This course varies from time to time, focusing on topics of interest to the faculty and students. It considers basic concepts such as information content, entropy and the Kullback-Leibler distance, as well as areas such as data compression and Shannon's Source Coding Theorem, coding, prefix codes, lossless channels and their capacity, and Shannon's Noisy Coding Theorem. The course will provide the student with an understanding of how self-interested behavior and coordination can be formally modeled and implemented in societies of artificial agents. The objective of the program … If you are going to have to basically home school yourself in computer science, there is no reason to pay tuition to Tulane. An introductory course on computer programming and problem-solving using computers. CMPS 3250  Theory of Computation  (3) Â. Prerequisite(s): MATH 2170 or CMPS 2170. 201 Lindy Claiborne Boggs Center This course details the theory and practice of designing effective information or scientific visualizations. Tulane pairs the resources of a large research university with the benefits of a small liberal arts college. An optional service learning component is included in the Software Studio (CMPS 3300/6300) course. Modern computer systems must take advantage not only of the latest hardware technology, but also of the ability to compute and communicate over a network. A bachelor’s program in computer science equips students with basic knowledge about information technology hardware and software, networks and security, and programming and analysis, with an … Among the topics covered are: "What is an intelligent artificial agent? Read more about how we calculate our rankings. Also, please visit this space often for information about the progress of Tulane Computer Science. At a practical level, students will design, implement, test and document their programs to learn introductory programming concepts, such as: data types and data structures (e.g. Departmental approval required. Prerequisite(s): (MATH 1160 or 1220) and (MATH 2170 or CMPS 2170). CMPS 6240  Intro to Machine Learning  (3) Â. Prerequisite(s): (CMPS 2170 or MATH 2170) and CMPS 2200. Many real world machine learning problems deal with mapping data to structured representations, and in the NLP domain the output structure represents lexical, syntactical or semantic aspects of the text. Topics include graph algorithms, randomized algorithms, parallel computing, linear programming and approximation algorithms. We are now in our eighth year, and our innovative program has reached some important milestones: Our program emphasizes both core computer science and its applications to related areas in the sciences and engineering, the health and social sciences, and the humanities. The aim of this course is to provide the student with an introduction to the main concepts and techniques playing a key role in the modern arena of artificial intelligence. An introduction on how graphical representations of data can be used to aid understanding. Topics will include linear and logistic regression, Lasso, preceptrons, deep neural networks, support vector machines, kernel methods, graphical models, principal and independent component analysis and Gaussian processes. Our goal is for our faculty and students to be recognized nationally and internationally for their research applying computer science to these areas. New Orleans, LA 70118 This course details the theory and practice of designing effective information or scientific visualizations. Assignments include practical problems drawn from various fields (such as biology, linguistics, graphics, and games). Course may be repeated up to unlimited credit hours. Topics covered will include geometric transformations, projections, raster algorithms, 3D object models (surface and volume), visible surface algorithms, texture mapping, lighting/shading, ray-tracing, anti-aliasing, and compositing. Topics covered include: sequence analysis and alignment, sequencing technologies, genome and metagenomic sequencing, protein structure and structure prediction, and phylogenetic analysis. CMPS 1500 is the first course for the Coordinate Major in Computer Science. Prerequisite(s): CMPS 1600. CMPS 6760  Distributed Systems  (3) Â. Prerequisite(s): CMPS 1600 and (MATH 2170 or CMPS 2170). CMPS 3360  Data Visualization  (3) Â. Under supervision of a faculty advisor in computer science, students use the tools of computer science to solve a problem from another discipline, usually their primary major area. will also be covered. At the beginning of the course the scope of the project will be determined by a project proposal prepared by the student. The student will prepare a final report that summarize the research methodologies and the research outcomes. ", problem solving using search and constraint satisfaction, uncertainty, Bayesian networks and probabilistic inference, supervised learning, planning, sequential decision problems, as well as several additional topics. Prerequisite(s): CMPS 2200. CMPS 3140  Intro Artificial Intelligence  (3) Â. This course covers fundamental algorithm design principles and data structures, basic notions of complexity theory, as well as an advanced introduction to parallel algorithms, randomized algorithms, and approximation algorithms. uncertainty in visualizations. CMPS 3280  Information Theory  (3) Â. This is the second of a two-semester course devoted to the development of the student’s capstone project, a required component of the Computer Science coordinate major. Covered topics include fundamental geometric algorithm design and analysis paradigms, geometric data structures for planar subdivisions and range searching, algorithms to compute the convex hull, Voronoi diagrams, and Delaunay triangulation, as well as selected advanced topics. The PDF will include all pages within the School of Medicine Catalog. CMPS 4730  Machine Learning and NLP  (3) Â. Department approval may be required. 504-865-5687. This course is an introduction to the theory of computation. Techniques covered in this course include discriminative and generative models including Structured Perceptron and Structured SVMs, Constrained Conditional Models, Probabilistic Graphical Models as well as Deep Learning techniques. Diversity is a highlight across our department: we have two female faculty members, four of our PhD students are women, and women make up a significant proportion of our undergraduate enrollment. The successful candidate will anchor our research activities by leading research collaborations within the department, in SSE, and across the other Tulane schools and colleges. This course is an introduction to logic and its applications in computer science. Toggle navigation. Computational Geometry is a young discipline which enjoys close relations to mathematics and to various application areas such as geometric databases, molecular biology, sensor networks, visualization, geographic information systems (GIS), VLSI, robotics, computer graphics and geometric modeling. 6823 St. Charles Avenue The content of this course varies from semester to semester. This course focuses on advanced techniques in the design and analysis of algorithms and illustrates how they are used in deriving a variety of now-classic results. It considers basic concepts such as information content, entropy and the Kullback-Leibler distance, as well as areas such as data compression and Shannon's Source Coding Theorem, coding, prefix codes, lossless channels and their capacity, and Shannon's Noisy Coding Theorem. This course is an introduction to computational methods in molecular biology. We are hiring! Prerequisite(s): (CMPS 2170 or MATH 2170) and CMPS 2200. Founder Chair, for which we anticipate hiring a senior researcher with international standing who works in an area related to data science. Courses taught abroad by non-Tulane faculty. Topics usually include: asymptotic analysis and big-O notation; divide-and-conquer algorithms; recurrences and the master method; greedy algorithms; graph algorithms (Breadth-First Search, Depth-First Search, Connectivity and Shortest Paths); dynamic programming; linear programming; lower bounds and computational complexity. CMPS 6620  Artificial Intelligence  (3) Â. 110 Gibson Hall The mission of the Information Technology Program at Tulane’s School of Professional Advancement is to prepare students who are professionally competent and able to make valuable contributions to an organization in the application of knowledge and skills in information technology to help in achieving organization goals. Computational Geometry  (3) Â. The objective of the course is to introduce students to the core concepts and analytic techniques in the design and analysis of computer networks and network protocols. Research toward completion of a masters degree. This course provides an introduction to geometric algorithms and geometric data structures. The techniques learned in this class have wide applications to all fields in engineering and science, where due to increasing sizes and complexity, data now demands effective presentation and analysis. Corequisite(s): CMPS 1501. We welcomed the third entering class for our PhD program last fall. This course is an introduction to several areas of mathematics that are particularly useful in computer science. Topics will include iso-surfacing, volume rendering, transfer functions, vector/tensor fields, topological analysis, large data visualization, and It also considers semantic security and analysis of secure information flow. Computational Geometry is a young discipline which enjoys close relations to mathematics and to various application areas such as geometric databases, molecular biology, sensor networks, visualization, geographic information systems (GIS), VLSI, robotics, computer graphics and geometric modeling. Example application areas include graph theory, discrete optimization, numeric and scientific computing and machine learning. ", problem solving using search and constraint satisfaction, uncertainty, Bayesian networks and probabilistic inference, supervised learning, planning, sequential decision problems, as well as several additional topics. Tulane doesn't have computer scientists around--they have people who use … Tulane Computer & Information Sciences Bachelor’s Program For the most recent academic year available, 72% of computer and information sciences bachelor's degrees went to men and 28% … This course is designed for graduate students interested in understanding the design of autonomous intelligent agents. The PhD Program in Computer Science guides students from beginning graduate study in Computer Science all the way through to completion of their dissertation research. CMPS 2301  Intro to Comp Sys & Netwk Lab  (0) Â, CMPS 2940  Transfer Coursework  (0-20) Â. Topics include graph algorithms, randomized algorithms, parallel computing, linear programming, and approximation algorithms. CMPS 3310  Logic in Computer Science  (3) Â. The topics covered include generative/discriminative and parametric/non-parametric supervised learning, including neural networks; unsupervised learning, including clustering, dimensionality reduction and kernel methods; learning theory, including tradeoffs, large margins and VC theory; reinforcement learning, including criteria for optimality, brute force methods, value function methods and direct policy search; feedforward/feedback adaptive control, direct/indirect adaptive control methods; and various applications. The PDF will include all pages within the School of Social Work Catalog. Details about interdisciplinary activities of the Computer Science graduate faculty are given below. MAS are playing an increasingly important role in Artificial Intelligence as distributed resources push for highly distributed forms of intelligence. will be used as case studies to help students establish a firm understanding of the philosophy and pitfalls in the design of computer systems when there is no global clock and when unpredictable failures and variable latency are the norm. Open to high-school students only, no prerequisites. Prerequisite(s): CMPS 1600. Departmental approval required. This course covers fundamental algorithm design principles and data structures, basic notions of complexity theory, as well as an advanced introduction to parallel algorithms, randomized algorithms, and approximation algorithms. biology, biochemistry, chemistry, economics, linguistics, mathematics, physics, and psychology). We have seven tenure-track/tenured faculty and two Professors of Practice. The primary focus of the course will be on understanding the divide-and-conquer, greedy and dynamic programming paradigms for algorithm design as well as the problem areas to which they can be applied. Download Academic Catalog The aim of this course is to provide the student with an introduction to the main concepts and techniques required for collecting, processing, and deriving insight into data. 72 of 821. This course emphasizes program design process, object-oriented software development approach, and practical programming skills that translate to programming in other modern languages. CMPS 3240  Intro to Machine Learning  (3) Â. Nicholas Mattei, an assistant professor of computer science at Tulane University, focuses much of his research on ethics in artificial intelligence. Course may be repeated up to unlimited credit hours. In this course, we will focus on the myriad of algorithms for analyzing numerous aspects of protein structure and protein-protein interactions. This is the second course in the introductory course sequence for Coordinate Major in Computer Science and is the continuation of CMPS 1500. This course provides an introduction to the fundamental concepts of machine learning and statistical pattern recognition. Prerequisite(s): CMPS 1500 and (CMPS 2170 or MATH 2170). This course studies the mathematics underlying computer security, including both public key and symmetric key cryptography, crypto-protocols and information flow. Course may be repeated up to unlimited credit hours. The PDF will include all pages within the School of Professional Advancement Catalog. Prerequisite(s): CMPS 2200. Ever since, Nick Altiero, dean of the School of Science and Engineering, has been … The Tulane Computer Science Department offers an Interdisciplinary PhD degree that focuses on the application of computer science and its principles to related areas. CMPS 6630  Computational Bio & Bioinform  (3) Â. We anticipate hiring several tenure-track/tenured faculty member this year and possible a third Professor of Practice. This course provides an introduction to geometric algorithms and geometric data structures. We will explain both how computer networks work using the Internet as the paradigm and why they work from an optimization and control perspective. It also considers semantic security and analysis of secure information flow. This is the first semester of a two-semester course devoted to the development of the student's capstone project, a required component of the Computer Science coordinate major. An introduction on how graphical representations of data can be used to aid understanding. Does not count toward Tulane GPA. 6823 St. Charles Avenue New Orleans, LA 70118 504-865-5000. This mission is accomplished by providing students with a challenging academic program of study, presented by a faculty of experienced information technology professionals and indus… Prerequisite(s): (CMPS 2170 or MATH 2170) and (CMPS 2200). Techniques covered in this course include discriminative and generative models including Structured Perceptron and Structured SVMs, Constrained Conditional Models, Probabilistic Graphical Models, as well as Deep Learning techniques. The particular technologies employed in the course may change in synchrony with changes in the software engineering field, currently the focus is on engineering software-as-a-service using Ruby for programming language and Rails for web development framework. CMPS 2300  Intro to Comp Sys & Networking  (3) Â. 126 SUBJECTS. This course is an advanced introduction to the area of computational complexity. CMPS 2200  Intro to Algorithms  (3) Â. Topics include: divide-and-conquer, dynamic programming, amortized analysis, graph algorithms, network flow, map reduce, and more advanced topics in approximation algorithms and randomized algorithms. The high-level goal of this course is to train students to be able to draw from a versatile set of skills, which in turn will provide a strong foundation for further study in computer science. He was an Assistant Professor of Computer Science and Electrical … (Photo by Paula Burch-Celentano) Mattei received an IBM … Automated methods to analyze protein structure make it possible to leverage information from previously solved structures, and to interpret experimental data in a principled way. Prerequisite(s): CMPS 1600. The course will provide the student with an understanding of how self-interested behavior and coordination can be formally modeled and implemented in societies of artificial agents. Working in teams, students apply a recognized software engineering methodology, a modern programming language, and software development tools (including an IDE, debugger, version control system, and testing framework) to design and implement a semester-long project – a software solution for a real-world problem. CMPS 2170  Intro to Discrete Math  (3) Â. The topics include an introduction to predicate and propositional logic, mathematical induction, combinatorics and counting, and discrete probability theory. Departmental approval required. Connect with Tulane School of Professional Advancement. Our recent undergraduates have found jobs in computer science and related areas, and several are pursuing PhD degrees at leading departments. This course emphasizes program design process, object-oriented software development approach, and practical programming skills that translate to programming in other modern languages. Topics covered will include geometric transformations, projections, raster algorithms, 3D object models (surface and volume), visible surface algorithms, texture mapping, lighting/shading, ray-tracing, anti-aliasing, and compositing. CMPS 4020  Capstone Project II  (2) Â. Research will be conducted on an individual basis with the faculty advisor. The Tulane Computer Science Department is housed in the School of Science and Engineering, which has strong research representation in a number of areas that are relevant to the searches we are … Prerequisite(s): (CMPS 2170 or MATH 2170) and (CMPS 2200). Most assignments in this course are programming assignments aimed to teach the students to express their ideas in efficient and elegant code; no prior programming experience is necessary to join and succeed in the course. CMPS 6310  Logic in Computer Science  (3) Â. Corequisite(s): CMPS 2301. The topics covered include soundness and completeness of propositional logic, predicate logic, linear time temporal logic and branching time temporal logics, and their expressive power, frameworks for software verification, Hoare triples, partial and total correctness, modal logics and agents, and binary decision diagrams. Download School of Social Work Catalog PDF. Prerequisite(s): CMPS 1500, 1600 and 2200. This is a project-oriented course on fundamentals of software development and software engineering. The second aim is to provide a more in depth discussion of selected MAS topics: game theory and voting from a computational point of view. This component provides a unique experience of communicating with a nontechnical customer, converting their requirements into technical specifications, working to meet those requirements, continuously refining those requirements, experiencing real-life associated technical challenges (such as environment incompatibility, difference in data formats, restricted access to data), preventing and resolving those challenges, and seeing a product come to life. An introductory course on computer programming, in which the students design, implement, test, and debug programs for computational problems using Python programming language. Prerequisite(s): CMPS 1600. 6823 St. Charles Avenue Prerequisite(s): (CMPS 2170 or MATH 2170) and CMPS 2200. Department of Computer Science; School of Science and Engineering; Tulane University; 307B Stanley Thomas Hall, 6823 St. Charles Avenue; New Orleans, LA 70118; Phone: (504) 247-1468 Fax: (504) 865-5786; Email: zzheng3 at tulane … Prerequisite(s): CMPS 1600 and (MATH 2170 or CMPS 2170). office: 6823 St. Charles Ave, 303C Stanley Thomas Hall, New Orleans, LA 70118 email: jhamm3 links: home | Google scholar | people and … The topics covered include soundness and completeness of propositional logic, predicate logic, linear time temporal logic and branching time temporal logics and their expressive power, frameworks for software verification, Hoare triples, partial and total correctness, modal logics and agents, and binary decision diagrams. CMPS 6150  Multi-agent Systems  (3) Â. Prerequisite(s): MATH 3050 or 3090. Prerequisite(s): (MATH 2170 or CMPS 2170) and CMPS 2200 and 2300. By solving practical, real-life problems in different programming languages and in different ways, students learn to select a language and approach most appropriate for the situation, and prepare to learn new languages independently. This course has two main goals. Transfer coursework at the 4000 level. Students work with a non-profit organization and develop a website to help them in their work. For more information about our program and to apply, follow the link under Academics. CMPS 1005  Python Programming  (3) Â. Techniques, ideas, and games read research papers, participate in active research projects conducted the. Problems using Python tulane computer science language progress of Tulane Computer Science graduate faculty are given below 7940Â! Please email me at mislove @ tulane.edu with your questions and comments develop. Gain experience in building 2D/3D interactive applications using OpenGL topics such as biology, biochemistry, chemistry, economics linguistics. Â. 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