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    by Marina 49 Lessons in , , ,

    Computational Science and Engineering I course,  previously called “Mathematical Methods for Engineers I“,  provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace’s equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and […]

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    by Marina 29 Lessons in

    Mathematical Methods for Engineers II is graduate-level course, which is a continuation of Mathematical Methods for Engineers I (18.085). Topics include numerical methods; initial-value problems; network flows; and optimization. Teaching Staff Prof. Gilbert Strang

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    by Marina 26 Lessons in

    Theory of City Form course covers theories about the form that settlements should take and attempts a distinction between descriptive and normative theory by examining examples of various theories of city form over time. Case studies will highlight the origins of the modern city and theories about its emerging form, including the transformation of the […]

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    by Marina 23 Lessons in

    Introduction to Building Technology course aims at providing a fundamental understanding of the physics related to buildings and to propose an overview of the various issues that have to be adequately combined to offer the occupants a physical, functional and psychological well-being. Students will be guided through the different components, constraints and systems of a […]

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    by Marina 15 Lessons in

    Advanced Analytic Methods in Science and Engineering course is a comprehensive treatment of the advanced methods of applied mathematics. It was designed to strengthen the mathematical abilities of graduate students and train them to think on their own. Teaching Staff Prof. Hung Cheng  

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    by Marina 15 Lessons in

    Mechanics and Design of Concrete Structures course provides students with a rational basis of the design of reinforced concrete members and structures through advanced understanding of material and structural behavior. The subject will be approached by looking into the behavior of reinforced concrete at different levels: material level (Micro-Cracking Mechanism, Multi-Axial Loading Responses, Failure Theories, […]

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    by Marina 26 Lessons in

    Introduction to Arithmetic Geometry course is an introduction to arithmetic geometry, a subject that lies at the intersection of algebraic geometry and number theory. Its primary motivation is the study of classical Diophantine problems from the modern perspective of algebraic geometry. Course Textbooks Fulton, William. Algebraic Curves: An Introduction to Algebraic Geometry. This book is […]

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    by Marina 18 Lessons in

    Project Management course focuses on the management and implementation of construction projects, primarily infrastructure projects. A project refers to a temporary piece of work undertaken to create a unique product or service. Whereas operations are continuous and repeating, projects are finite and have an end date. Projects bring form or function to ideas or need. […]

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    by Marina 40 Lessons in

    Linear Algebra course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines. Linear algebra is a branch of mathematics that studies systems of linear equations and the properties of matrices. The concepts of linear algebra are extremely useful in physics, economics and social sciences, natural sciences, and engineering. Due to its broad […]

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    by Marina 15 Lessons in

    Math 131B: Introduction to Probability and Statistics is an introductory course covering basic principles of probability and statistical inference. Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference. Teaching Staff Michael C. Cranston Ph.D.

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    by Marina 16 Lessons in

    Math 131A: Introduction to Probability and Statistics is an introductory course covering basic principles of probability and statistical inference. Topics covered in this course: Axiomatic definition of probability, random variables, probability distributions, expectation. Teaching Staff Michael C. Cranston Ph.D.