Среди жителей Кёнигсберга была распространена такая практическая головоломка: можно ли пройти по всем мостам через реку Преголя, не проходя ни по одному из них дважды? В 1736 году выдающийся математик Леонард Эйлер заинтересовался задачей и в письме другу привел строгое доказательство того, что сделать это невозможно. В том же году он доказал замечательную формулу, которая связывает число вершин, граней и ребер многогранника в трехмерном пространстве. Формула таинственным образом верна и для графов, которые называются "планарными". Эти два результата заложили основу теории графов и неплохо иллюстрируют направление ее развития по сей день. Граф как математический объект оказался полезным во многих теоретических и практических задачах. Наверное, дело в том, что сложность его структуры хорошо отвечает возможностям нашего мозга: это структура наглядная и понятно устроенная, но, с другой стороны, достаточно богатая, чтобы улавливать многие нетривиальные явления. Если говорить о приложениях, то, конечно, сразу же на ум приходят большие сети: Интернет, карта дорог, покрытие мобильной связи и т.п. В основах поисковых машин, таких, как Yandex и Google, лежат алгоритмы на графах. Помимо computer science, графы активно используются в биоинформатике, химии, социологии. Этот курс служит введением в современную теорию графов. Мы, конечно, обсудим классические задачи, но и поговорим про более недавние результаты и тенденции, например, про экстремальную теорию графов. Материал изложен с самых основ и на доступном языке. Целью этого курса является не только познакомить вас с вопросами и методами теории графов, но и развить у неподготовленных слушателей культуру математического мышления. Поэтому курс доступен широкому кругу слушателей. Для освоения материала будет достаточно знания математики на хорошем школьном уровне и базовых знаний комбинаторики. Курс состоит из 7 учебных недель и экзамена. Для успешного решения большинства задач из тестов достаточно освоить материал, рассказанный на лекциях. На семинарах разбираются и более сложные задачи, которые смогут заинтересовать слушателя, уже знакомого с основами теории графов.

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences. Distinguishing features of the course include: 1) the introduction and use of Taylor series and approximations from the beginning; 2) a novel synthesis of discrete and continuous forms of Calculus; 3) an emphasis on the conceptual over the computational; and 4) a clear, dynamic, unified approach. In this second part--part two of five--we cover derivatives, differentiation rules, linearization, higher derivatives, optimization, differentials, and differentiation operators.

En este tercer curso de acceso gratuito* del programa especializado Educación Matemática para profesores de primaria, conocerás los conceptos y técnicas para planificar e implementar tus clases. El curso tiene una duración aproximada de seis semanas, con una dedicación promedio de 4 horas semanales. Todas las evaluaciones tienen retroalimentación y podrás descargar la mayoría de los recursos del curso. Este curso se basa en la información y los conocimientos que desarrollamos en los dos cursos anteriores de nuestro programa: Contenido de las matemáticas de primaria y Aprendizaje de las matemáticas de primaria. Te recomendamos tomar esos dos cursos antes de tomar este. Estos cursos también están disponibles en Coursera. Este curso incluye videos de presentación y explicación de los temas, actividades de aprendizaje y evaluación, revisión por pares, mapas conceptuales, y bibliografía adicional. La evaluación está diseñada para que recibas realimentación que queda registrada en la plataforma, de manera que puedas continuar con tu progreso al conectarte nuevamente. Puedes descargar la mayoría de los contenidos para que los uses sin conexión a Internet. La Universidad de los Andes desarrolló el programa especializado Educación Matemática para profesores de primaria gracias al apoyo de United Way Colombia, el Fondo Puentes de Caña, la Fundación SM y la Fundación Compartir, con la colaboración de la Fundación de la Universidad de los Andes en Nueva York, Estados Unidos. * Al inscribirte al curso, puedes elegir la opción que más te interese: sin certificación, en cuyo caso tendrás acceso a todo el contenido del curso de forma gratuita; o con certificación, en cuyo caso deberás aprobar un cuestionario de evaluación por módulo y cumplir con los demás requisitos de la plataforma: hacer la verificación de identidad al presentar las evaluaciones obligatorias, lograr el porcentaje mínimo para pasar el curso y pagar directamente a Coursera el precio de la certificación anunciado en la plataforma.

Vector Calculus for Engineers covers both basic theory and applications. In the first week we learn about scalar and vector fields, in the second week about differentiating fields, in the third week about multidimensional integration and curvilinear coordinate systems. The fourth week covers line and surface integrals, and the fifth week covers the fundamental theorems of vector calculus, including the gradient theorem, the divergence theorem and Stokes’ theorem. These theorems are needed in core engineering subjects such as Electromagnetism and Fluid Mechanics. Instead of Vector Calculus, some universities might call this course Multivariable or Multivariate Calculus or Calculus 3. Two semesters of single variable calculus (differentiation and integration) are a prerequisite. The course is organized into 53 short lecture videos, with a few problems to solve following each video. And after each substantial topic, there is a short practice quiz. Solutions to the problems and practice quizzes can be found in instructor-provided lecture notes. There are a total of five weeks to the course, and at the end of each week there is an assessed quiz. Download the lecture notes: http://www.math.ust.hk/~machas/vector-calculus-for-engineers.pdf Watch the promotional video: https://youtu.be/qUseabHb6Vk

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences. Distinguishing features of the course include: 1) the introduction and use of Taylor series and approximations from the beginning; 2) a novel synthesis of discrete and continuous forms of Calculus; 3) an emphasis on the conceptual over the computational; and 4) a clear, dynamic, unified approach. In this fourth part--part four of five--we cover computing areas and volumes, other geometric applications, physical applications, and averages and mass. We also introduce probability.

The lectures of this course are based on the first 11 chapters of Prof. Raymond Yeung’s textbook entitled Information Theory and Network Coding (Springer 2008). This book and its predecessor, A First Course in Information Theory (Kluwer 2002, essentially the first edition of the 2008 book), have been adopted by over 60 universities around the world as either a textbook or reference text. At the completion of this course, the student should be able to: 1) Demonstrate knowledge and understanding of the fundamentals of information theory. 2) Appreciate the notion of fundamental limits in communication systems and more generally all systems. 3) Develop deeper understanding of communication systems. 4) Apply the concepts of information theory to various disciplines in information science.

As rates of change, derivatives give us information about the shape of a graph. In this course, we will apply the derivative to find linear approximations for single-variable and multi-variable functions. This gives us a straightforward way to estimate functions that may be complicated or difficult to evaluate. We will also use the derivative to locate the maximum and minimum values of a function. These optimization techniques are important for all fields, including the natural sciences and data analysis. The topics in this course lend themselves to many real-world applications, such as machine learning, minimizing costs or maximizing profits.

Algebra is one of the definitive and oldest branches of mathematics, and design of computer algorithms is one of the youngest. Despite this generation gap, the two disciplines beautifully interweave. Firstly, modern computers would be somewhat useless if they were not able to carry out arithmetic and algebraic computations efficiently, so we need to think on dedicated, sometimes rather sophisticated algorithms for these operations. Secondly, algebraic structures and theorems can help develop algorithms for things having [at first glance] nothing to do with algebra, e.g. graph algorithms. One of the main goals of the offered course is thus providing the learners with the examples of the above mentioned situations. We believe the course to contain much material of interest to both CS and Math oriented students. The course is supported by programming assignments.

In this introductory course on Ordinary Differential Equations, we first provide basic terminologies on the theory of differential equations and then proceed to methods of solving various types of ordinary differential equations. We handle first order differential equations and then second order linear differential equations. We also discuss some related concrete mathematical modeling problems, which can be handled by the methods introduced in this course. The lecture is self contained. However, if necessary, you may consult any introductory level text on ordinary differential equations. For example, "Elementary Differential Equations and Boundary Value Problems by W. E. Boyce and R. C. DiPrima from John Wiley & Sons" is a good source for further study on the subject. The course is mainly delivered through video lectures. At the end of each module, there will be a quiz consisting of several problems related to the lecture of the week.

This course is an important part of the undergraduate stage in education for future economists. It's also useful for graduate students who would like to gain knowledge and skills in an important part of math. It gives students skills for implementation of the mathematical knowledge and expertise to the problems of economics. Its prerequisites are both the knowledge of the single variable calculus and the foundations of linear algebra including operations on matrices and the general theory of systems of simultaneous equations. Some knowledge of vector spaces would be beneficial for a student. The course covers several variable calculus, both constrained and unconstrained optimization. The course is aimed at teaching students to master comparative statics problems, optimization problems using the acquired mathematical tools. Home assignments will be provided on a weekly basis. The objective of the course is to acquire the students’ knowledge in the field of mathematics and to make them ready to analyze simulated as well as real economic situations. Students learn how to use and apply mathematics by working with concrete examples and exercises. Moreover this course is aimed at showing what constitutes a solid proof. The ability to present proofs can be trained and improved and in that respect the course is helpful. It will be shown that math is not reduced just to “cookbook recipes”. On the contrary the deep knowledge of math concepts helps to understand real life situations. Do you have technical problems? Write to us: [email protected]