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As we increase our online activity, so too do we increase the amount of personal data that we're sharing, often without realizing it. At the end of this course you will be able to develop computer tools for scientific applications, such as the structuring and analysis of experimental data. Specifications. Office of the Faculty Registrar Advanced algorithm design techniques, with emphasis on the role that geometry, approximation, randomization, and parallelism play in modern algorithms. Software systems are complex and interesting. Faculty of Arts & Science Viewbook 7. What these tasks have in common has little to do with the physics or electronics of computers; what matters is that they can be formulated as some sort of computation. Formal theories and the Gödel Incompleteness Theorem. To qualify for any degree you must complete at least one full course equivalent in each of these three areas, for a total of 3.0 full course equivalents. Introduction to abstraction and rigour. Please consult the advice about graduate study included with the description of the Specialist program in Computer Science. Organized by a wide variety of case studies drawn from current events, we'll study how personal data can be collected and tracked, how personal and social factors may influence our own decisions about whether and how much to share our data, and what broader political and legal tools are used to either protect or subvert individual privacy. First day of course enrolment (in Arts & Science courses) for UTM and UTSC students: September 2, 2020 A. Farahmand, PhD U of T Mississauga Viewbook 6. Professor and Chair of the Department R. Pysklywec, M Sc, Ph D Professor and Chair of the Department (Interim) G.S. Students will be advised to develop domain expertise in at least one area where Data Science is applicable, by taking a sequence of courses in that area throughout their program. They are full-credit or half-credit courses that focus on discussion of issues, questions and controversies surrounding a particular discipline (or several disciplines) in a small-group setting that encourages the development of critical thinking, writing skills, oral presentation and research methods. Data science workflows will be integrated throughout the course. 3.0 credits from the following: with at least 0.5 credit from a 400-level CSC/BCB course, at least 1.0 additional credit from 300-/400-level CSC/BCB courses, and at least 0.5 additional credit from a 300-/400-level course. The relational data model. This course is intended for economics, mathematics, and computer science students. Software techniques in a Unix-style environment, using scripting languages and a machine-oriented programming language (typically C). The focus covers the algorithm foundations of web and internet technologies, as well as implementation and system architecture. Also ask for advice even if you don’t have transfer credits yet but are considering degree study at the University of Toronto. … G. Hirst, MSc, PhD, Professor, Teaching Stream and Associate Chair (Undergraduate Studies)  Neural networks for unsupervised and reinforcement learning. S. McIlraith, MMath, PhD  W. Enright, MSc, PhD (University of Toronto Scarborough)  The Data Science Specialist program prepares students for work in the Data Science industry or government and for graduate studies in Data Science, Computer Science, or Statistics. ( MAT157Y1 grades will be adjusted to account for the course's greater difficulty.) Predicate calculus, including the completeness, compactness, and Lowenheim-Skolem theorems. Obtaining these minimum grades does not guarantee admission to the program. These basic tools are required in order to first pose computational vision problems, and then develop and test algorithms for the solution to those problems. The successful student will combine their expertise in computer and statistical science to produce and communicate analyses of complex large-scale datasets. https://undergrad.engineering.utoronto.ca/exams/schedules-location Services, programs, and co-curricular opportunities available to current students: health and wellness, career support, accessibility services, athletics, creative arts, student clubs and organizations, and more. P. Gries, MEng  Concepts underlying the development of programs that operate on the web; survey of technological alternatives; greater depth on some technologies. Despite the name, Computer Science is not really a science of computers at all. M. Craig, MSc  The numerical methods are analyzed and their performance (e.g. Requests for admission will be considered in the first program request period only. N.E.W. M. Erdogdu, PhD D. Lie, PhD  Student Services & Campus Life. If they do state a Breadth Requirement, h alf-courses offer 0.5 credits towards only one of the categories; full-courses offer either 0.5 credits in two … Searching, sorting, and complexity. Artificial Intelligence (AI) is aimed at understanding and replicating the computational processes underlying intelligent behaviour. Topics from: database design, considerations in numerical calculation, using UNIX/LINUX systems. Image synthesis and image analysis aimed at students with an interest in computer graphics, computer vision, or the visual arts. An open team project is done in the last few laboratory sessions. The courses are as follows: from CSC148H1 to CSC108H1, from CSC240H1 to CSC165H1 (or to CSC236H1 if you have already passed CSC165H1 with at least 60%), and from CSC265H1 to CSC263H1. F. Roth, PhD  Connected device charachteristics and the hardware and software ramifications. A. Gupta, PhD The course requires the ability to use differential calculus in several variables and linear algebra. First day of course enrolment for St. George campus (downtown) students who are not enrolled the Faculty of Arts & Science: August 7, 2020. Computers are quite remarkable electronic devices, but even more remarkable is what they can be made to do: simulate the flow of air over a wing, manage communication over the Internet, control the actions of a robot, synthesize realistic images, play grandmaster-level chess, and on and on. A. Anderson, PhD (University of Toronto Scarborough) This course assumes university-level experience with proof techniques and algorithmic complexity as provided by CSC165H1. Details at https://www.artsci.utoronto.ca/current/academics/research-opportunities/research-opportunities-program. An introduction to neural networks and deep learning. Faculty of Arts & Science: Rotman Commerce Viewbook 8. Part of Computer Science is concerned with understanding just how far computational ideas can be applied. The official source for these dates is your division’s academic calendar. Restricted to first-year students. Press question mark to learn the rest of the keyboard shortcuts. Ontario Emergency Stay-at-home Order Update. Basic software development infrastructure; requirements elicitation and tracking; estimation and prioritization; teamwork skills; basic UML; design patterns and refactoring; security, discussion of ethical issues, and professional responsibility. Introduction to techniques involving natural language processing and speech in applications such as information retrieval, speech recognition and synthesis, machine translation, summarization, and dialoque. APM462H1, COG250Y1, CSC384H1, CSC485H1, CSC486H1, ECE216H1, PHL232H1, PHY385H1, PSL440Y1, PSY270H1, PSY280H1, STA257H1/​ STA261H1. Indeed the application of computers in activities like these has affected most areas of modern life. While the field has seen some successful impossibility results, there are still many problems (such as those underlying modern cryptography and security) for which we do not know either efficient algorithms or strong lower bounds! An introduction to software development on the web. That is, we attempt to clearly define computational problems for various steps of the overall process, and then show how these problems can be tackled with appropriate algorithms. Students must have completed 4.0 credits and meet the requirements listed below to enrol. There is no need to replace the missing half-credit for program completion; however, please base your course choice on what you are ready to take, not on "saving" a half-credit. E. Grinspun, PhD Winter 2021 at the Faculty of Applied Science & Engineering Latest information for Engineering students, faculty & staff Learn more » UCheck: Students, staff and faculty must complete a COVID-19 self-assessment before coming to campus. This online calendar is the most current version of the Graduate Academic Calendar and Course Catalogue. 2020-2021 Calendar Ontario’s response to the COVID-19 pandemic continues to evolve. MAT137Y1/​ MAT157Y1; MAT223H1/​ MAT240H1 ( MAT240H1 is recommended); STA130H1; ( CSC108H1, CSC148H1)/ ( CSC110Y1, CSC111H1) E. Mendelsohn, MSc, PhD (Professor Emeritus) (University of Toronto Scarborough)  Other relevant Computer Science courses, depending on the student's interests, include other courses in artificial intelligence such as CSC384H1 or CSC420H1. Please refer to the Arts & Science Registration Instructions and Timetable for prerequisite waiver deadlines. Modern database applications: data mining, data warehousing, OLAP, data on the web. 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