Overview of MSc in Computer Science course at McGill, i.e., McGill University, Montreal with upcoming application deadlines, average profile of admits, tuition fee, average salary and course duration Credits, All content related requests should be sent to, at least 14 credits of COMP (or approved) Complementary Naming services. COMP 680 Mining Biological Sequences (4 credits) Background in calculus, linear algebra, probability at the level of MATH 222, MATH 223, MATH 323, respectively. Gene-finding with hidden Markov models and variants. COMP 557 Fundamentals of Computer Graphics (4 credits) Computer Science (Sci) : Conservative and optimistic synchronization involved in executing a discrete event simulation on a distributed platform (e.g. For the Master's Graduate Program Director, please contact Prof Muthucumaru Maheswaran. The progress form below must be filled by the student, discussed / M.Sc. [2] Lawrence W Barsalou. COMP 529 Software Architecture (4 credits) McGill Data Science researchers investigate data-mining and modeling methods that can be applied to solve current problems in domains ranging from the basic sciences to health care, education, economics, public policy, social media, cultural analysis, the environment, and beyond. COMP 618 Bioinformatics: Functional Genomics (3 credits) Applications to knowledge bases, data mining, semistructured data, Internet DB. COMP 554 Approximation Algorithms (4 credits) COMP 560 Graph Algorithms and Applications (3 credits) Run-time implementation of various programming language constructs. Some background in Artificial Intelligence is recommended, e.g. of the Theory, Systems, and Application areas. year (except the first year) before September 30th, and submitted to Ann COMP 535 Computer Networks 1 (4 credits) Web, CORBA). Offered by: Computer Science (Faculty of Science). The maximum COMP 612 Database Programming Principles (4 credits) listed below such as a new course or a 500 level Topics courses follows the Computer Science (Sci) : Algorithms for connectivity, partitioning, clustering, colouring and matching. or Ph.D. Committee respectively. COMP 655 Distributed Simulation (4 credits) at least 28 credits of COMP (or approved) Complementary courses at Instructors: Ravanbakhsh, Mohsen (Fall) Rabbany, Reihaneh (Winter), Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent. Authors: Yi Tian Xu, Yaqiao Li, David Meger Abstract: Inspired by ideas in cognitive science, we propose a novel and general approach to solve human motion understanding via pattern completion on a … Instructors: Waldispuhl, Jérôme (Winter). Adaptive estimation, GPS measurements and mathematical models for positioning. three areas of Theory, Systems, and Applications. Topics include: randomized algorithms, network optimization, linear programming and semi definite programming techniques, the game theoretic method, the primal-dual method, and metric embeddings. At least 14 credits of COMP (or approved by MSc Graduate Program Director) 27, 2020) (, Graduate Admissions and Application Procedures, Graduate Student Services and Information, Information on Research Policies and Guidelines, Patents, Postdocs, Associates, Trainees, COMP 602 Computer Science Seminar 1 (1 credit), COMP 603 Computer Science Seminar 2 (1 credit), COMP 523 Language-based Security (3 credits), COMP 524 Theoretical Foundations of Programming Languages (3 credits), COMP 527 Logic and Computation (3 credits), COMP 531 Advanced Theory of Computation (3 credits), COMP 547 Cryptography and Data Security (4 credits), COMP 552 Combinatorial Optimization (4 credits), COMP 553 Algorithmic Game Theory (4 credits), COMP 554 Approximation Algorithms (4 credits), COMP 560 Graph Algorithms and Applications (3 credits), COMP 566 Discrete Optimization 1 (3 credits), COMP 567 Discrete Optimization 2 (3 credits), COMP 610 Information Structures 1 (4 credits), COMP 627 Theoretical Programming Languages (4 credits), COMP 642 Numerical Estimation Methods (4 credits), COMP 647 Advanced Cryptography (4 credits), COMP 649 Quantum Cryptography (4 credits), COMP 690 Probabilistic Analysis of Algorithms (4 credits), COMP 760 Advanced Topics Theory 1 (4 credits), COMP 761 Advanced Topics Theory 2 (4 credits), COMP 529 Software Architecture (4 credits), COMP 533 Model-Driven Software Development (3 credits), COMP 575 Fundamentals of Distributed Algorithms (3 credits), COMP 612 Database Programming Principles (4 credits), COMP 614 Distributed Data Management (4 credits), COMP 621 Program Analysis and Transformations (4 credits), COMP 655 Distributed Simulation (4 credits), COMP 667 Software Fault Tolerance (4 credits), COMP 762 Advanced Topics Programming 1 (4 credits), COMP 763 Advanced Topics Programming 2 (4 credits), COMP 764 Advanced Topics Systems 1 (4 credits), COMP 765 Advanced Topics Systems 2 (4 credits), COMP 521 Modern Computer Games (4 credits), COMP 522 Modelling and Simulation (4 credits), COMP 526 Probabilistic Reasoning and AI (3 credits), COMP 546 Computational Perception (4 credits), COMP 550 Natural Language Processing (3 credits), COMP 551 Applied Machine Learning (4 credits), COMP 557 Fundamentals of Computer Graphics (4 credits), COMP 558 Fundamentals of Computer Vision (4 credits), COMP 559 Fundamentals of Computer Animation (4 credits), COMP 561 Computational Biology Methods and Research (4 credits), COMP 564 Advanced Computational Biology Methods and Research (3 credits), COMP 579 Reinforcement Learning (4 credits), COMP 618 Bioinformatics: Functional Genomics (3 credits), COMP 680 Mining Biological Sequences (4 credits), COMP 766 Advanced Topics Applications 1 (4 credits), COMP 767 Advanced Topics: Applications 2 (4 credits). mutual exclusion, concurrency control). COMP 610 Information Structures 1 (4 credits) 咏月弹烟丝, 斟风醉雪洋. The courses must meet the same Breadth Requirement as in the Algorithms for special classes of graphs. Situated conceptualization. in Computer Engineering program and download course brochure. Computer Science (Sci) : Study of elementary data structures: lists, stacks, queues, trees, hash tables, binary search trees, red-black trees, heaps. Each student must meet annually with his/her supervisor or co-supervisors to Network simplex method. Model dependent measures of computational complexity. Computer Science (Sci) : The structure of a compiler. Applications in computational geometry and in game tree searching. Distributed file systems. Students admitted to "PhD1" must complete four years of residency (eight terms), plus one more year as a full-time student, while students admitted to "PhD2" must complete only three years (six terms) of residency, plus one more year as a ful… Computer Science (Sci) : Designing and programming reliable numerical algorithms. COMP 642 Numerical Estimation Methods (4 credits) COMP 522 Modellin and Simulation (4 credits) COMP 552 Combinatorial Optimization (4 credits) Prerequisites: COMP 360 or COMP 362, MATH 323. Instructors: D'silva, Joseph (Winter). Alternatively, A progress form must be filled each This program is offered in coursework and research-based. Excellent M.Sc. Quantum encryption, error-correcting codes and authentication. The category of any course not Such applicants must have completed a minimum of two and a COMP 647 Advanced Cryptography (4 credits) Complementary courses must programs are designed to take between 1.5 and 2 years. research. Computer Science student Jasmine Wang is among 154 picked, out of 3,600 applicants worldwide, for the distinguished program at Beijing’s Tsinghua University reporter.mcgill.ca Computer science undergrad wins Schwarzman Scholarship - McGill Reporter Strong background in algorithms and/or mathematics. The degree in Computer Science. Data replication and caching. More information on this program can be found at our B.Sc/M.Sc (Thesis) Track page, COMP 558 Fundamentals of Computer Vision (4 credits) general pattern of the existing courses. Prerequisite: COMP 362 or MATH 350 or MATH 454 or MATH 487, or instructor permission, Restriction: Not open to students who are taking or have taken MATH 553. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Both satisfy a Computer Science Breadth Requirement, with at least one course in two remote method invocation, group communication). If you are a McGill undergrad, then you can consider applying for the B.Sc. should follow the should take the Seminar courses COMP 602 (Fall) and 603 (Winter). of Research Project course credits) toward their M.Sc. Quantum bit commitment, zero-knowledge and oblivious transfer. Advanced data structures including binomial heaps, Fibonacci heaps, disjoint set structures, and splay trees. Lexical analysis. Prerequisites: COMP 362 or MATH 350 or permission of instructor. Prerequisite: COMP 547 and permission of the instructor. Committee of the School of Computer Science, in agreement with the McGill's Graduate and Postdoctoral Studies office, uses the following equivalencies by default (finer gradings not shown): Prerequisite: A university level course in machine learning such as COMP 451 or COMP 551. Computational morphology, language modelling, syntactic parsing, lexical and compositional semantics, and discourse analysis. supervisor, and the Progress Report are given below. Emphasis on physics of image formation, sensory signal processing, neural pathways and computation, psychophysical methods. Students who began Applications to large simulations (networks, VLSI, virtual environments). Computer Science (Sci) : An overview of state-of-the-art algorithms used in machine learning, including theoretical properties and practical applications of these algorithms. The following is a list of all the materials that should be uploaded to complete the on-line application. COMP 525 Formal Verification (3 credits) I am currently pursuing Master's in Computer Science at McGill University and MILA, where I am working under the supervision of Dr. Doina Precup.I am fascinated by the problem of Model Based Reinforcement Learning which provides an elegant way of performing planning and learning and am working on efficient approaches for modeling reward and state transition distributions. Applications of linear programming. Non-Thesis program will be sometimes referred to as the Project option since it Master’s (M.Sc.) If there are Instructors: Maheswaran, Muthucumaru (Winter). This program is offered in coursework and research-based. Topics include: polyhedral methods, network optimization, the ellipsoid method, graph algorithms, matroid theory and submodular functions.
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