Online courses directory (418)
This course is an introduction to the key ideas and principles of the collection, display, and analysis of data to guide you in making valid and appropriate conclusions about the world.
This course will cover the very basic ideas in optimization. Topics include the basic theory and algorithms behind linear and integer linear programming along with some of the important applications. We will also explore the theory of convex polyhedra using linear programming.
Une fonction discontinue peut-elle être solution d'une équation différentielle? Comment définir rigoureusement la masse de Dirac (une "fonction" d'intégrale un, nulle partout sauf en un point) et ses dérivées? Peut-on définir une notion de "dérivée d'ordre fractionnaire"? Cette initiation aux distributions répond à ces questions - et à bien d'autres.
這是一個機率的入門課程,著重的是教授機率基本概念。另外我們的作業將搭配臺大電機系所開發的多人競技線上遊戲方式,讓同學在遊戲中快樂的學習,快速培養同學們對於機率的洞察力與應用能力。
Curso diseñado para facilitar la entrada del estudiante en los cursos de cálculo de primer semestre de prácticamente cualquier grado universitario, con especial énfasis en Ciencias e Ingeniería.
Minima, maxima, and critical points. Rates of change. Optimization. Rates of change. L'Hopital's rule. Mean value theorem. Minima, maxima and critical points. Testing critical points for local extrema. Identifying minima and maxima for x^3 - 12x - 5. Concavity, concave upwards and concave downwards intervals. Recognizing concavity exercise. Recognizing concavity. Inflection points. Graphing using derivatives. Another example graphing with derivatives. Minimizing sum of squares. Optimizing box volume graphically. Optimizing box volume analytically. Optimizing profit at a shoe factory. Minimizing the cost of a storage container. Expression for combined area of triangle and square. Minimizing combined area. Rates of change between radius and area of circle. Rate of change of balloon height. Related rates of water pouring into cone. Falling ladder related rates. Rate of change of distance between approaching cars. Speed of shadow of diving bird. Mean Value Theorem. Introduction to L'H
Learn how to apply mathematical methods to philosophical problems and questions.
在社会学、心理学、教育学、经济学、管理学、市场学等研究领域的数据分析中,结构方程建模是当前最前沿的统计方法中应用最广、研究最多的一个。它包含了方差分析、回归分析、路径分析和因子分析,弥补了传统回归分析和因子分析的不足,可以分析多因多果的联系、潜变量的关系,还可以处理多水平数据和纵向数据,是非常重要的多元数据分析工具。本课程系统地介绍结构方程模型和LISREL软件的应用,内容包括:结构方程分析(包括验证性因子分析)的基本概念、统计原理、在社会科学研究中的应用、常用模型及其LISREL程序、结果的解释和模型评价。学员应具备基本的统计知识(如:标准差、t-检验、相关系数),理解回归分析和因子分析的概念。 注:本课程配套教材为《结构方程模型及其应用》(以LISREL软件为例)。
In questo corso imparerete i Principi che stanno alla base della Fisica del XX secolo, cioè della Relatività e la Meccanica Quantistica, e come sia cambiata la nostra visione del mondo.
2.01x introduces principles of structural analysis and strength of materials in applications to three essential types of load-bearing elements: bars in axial loading, axisymmetric shafts in torsion, and symmetric beams in bending.
The course covers fundamental concepts of continuum mechanics, including internal resultants, displacement fields, stress, and strain.
While emphasizing analytical techniques, the course also provides an introduction to computing environments (MATLAB) and numerical methods (Finite Elements: Akselos)
This course is based on the first subject in solid mechanics for MIT Mechanical Engineering students. Join them and learn how to predict linear elastic behavior, and prevent structural failure, by relying on the notions of equilibrium, geometric compatibility, and constitutive material response.
El curso propone un acercamiento a la Matemática Preuniversitaria donde el contexto del movimiento en línea recta dará significado al conocimiento y la tecnología será el medio para interactuar con el mismo.
This course analyzed the basic techniques for the efficient numerical solution of problems in science and engineering. Topics spanned root finding, interpolation, approximation of functions, integration, differential equations, direct and iterative methods in linear algebra.
The foundations of Pre-Algebra from The Khan Academy.
This course introduces three main types of partial differential equations: diffusion, elliptic, and hyperbolic. It includes mathematical tools, real-world examples and applications.
This course covers vector and multi-variable calculus. It is the second semester in the freshman calculus sequence. Topics include vectors and matrices, partial derivatives, double and triple integrals, and vector calculus in 2 and 3-space.
MIT OpenCourseWare offers another version of 18.02, from the Spring 2006 term. Both versions cover the same material, although they are taught by different faculty and rely on different textbooks. Multivariable Calculus (18.02) is taught during the Fall and Spring terms at MIT, and is a required subject for all MIT undergraduates.
This course emphasizes concepts and techniques for solving integral equations from an applied mathematics perspective. Material is selected from the following topics: Volterra and Fredholm equations, Fredholm theory, the Hilbert-Schmidt theorem; Wiener-Hopf Method; Wiener-Hopf Method and partial differential equations; the Hilbert Problem and singular integral equations of Cauchy type; inverse scattering transform; and group theory. Examples are taken from fluid and solid mechanics, acoustics, quantum mechanics, and other applications.
This course introduces the basic computational methods used to understand the cell on a molecular level. It covers subjects such as the sequence alignment algorithms: dynamic programming, hashing, suffix trees, and Gibbs sampling. Furthermore, it focuses on computational approaches to: genetic and physical mapping; genome sequencing, assembly, and annotation; RNA expression and secondary structure; protein structure and folding; and molecular interactions and dynamics.
Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course.
This graduate-level course covers Lebesgue's integration theory with applications to analysis, including an introduction to convolution and the Fourier transform.
ALISON.com's free online Diploma in Mathematics course gives you comprehensive knowledge and understanding of key subjects in mathematics. This course covers calculus, geometry, algebra, trigonometry, functions, vectors, data distributions, probability and probability and statistics. Math qualifications are in great demand from employers and this math course will greatly enhance your career prospects.<br />
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