Courses tagged with "Nutrition" (6413)

This self-paced course provides participants with the opportunity to explore, assess, and document learning mastered through a variety of life experiences.

Discover how businesses function and interact with the wider socio-economic environment. In association with ACCA.

The world’s greatest orchestras have the incredible ability to sound so unified they feel like one single instrument. Listening to the music of an orchestra can feel invigorating, exciting, and life-affirming all at the same time. But how do you learn to hear and appreciate the nuances of each instrument? How have the instruments that make up an orchestra evolved and improved over time?

Dr. L Michael Griffel, Chair of Juilliard’s Music History Department, takes you on a journey into the orchestra and introduces you to the history of its principal instruments.

You will learn about each instrument, from violin to timpani, and will gain the ability to recognize their individual sounds and textures when listening to any orchestral music.

Through four modules you will discover the four families of instruments: strings, woodwinds, brass, and percussion, giving you confidence to further discover the music of the orchestra. No prior musical experience necessary.

In this interactive pre-Calculus course, you will deepen and extend your knowledge of functions, graphs, and equations from high school algebra and geometry courses so you can successfully work with the concepts in a rigorous university-level calculus course. This course is designed to engage learners in the “doing” of mathematics, emphasizing conceptual understanding of mathematical definitions and student development of logical arguments in support of solutions. The course places major emphasis on why the mathematics topics covered work within the discipline, as opposed to simply the mechanics of the mathematics.

We will present the state of the art energy minimization algorithms that are used to perform inference in modern artificial vision models: that is, efficient methods for obtaining the most likely interpretation of a given visual input. We will also cover the popular max-margin framework for estimating the model parameters using inference.

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming.

Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?

Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).

Part 1 of this course analyzes signals and systems in the time domain. Part 2 covers frequency domain analysis.

Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). Part 1 is a prerequisite for Part 2. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.

Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?

Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).

Part 1 of this course analyzes signals and systems in the time domain. Part 2 covers frequency domain analysis.

Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). Part 1 is a prerequisite for Part 2. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.

This class addresses the representation, analysis, and design of discrete time signals and systems. The major concepts covered include: Discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flowgraph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multirate techniques; Hilbert transforms; Cepstral analysis and various applications.

Acknowledgements

I would like to express my thanks to Thomas Baran, Myung Jin Choi, and Xiaomeng Shi for compiling the lecture notes on this site from my individual lectures and handouts and their class notes during the semesters that they were students in the course. These lecture notes, the text book and included problem sets and solutions will hopefully be helpful as you learn and explore the topic of Discrete-Time Signal Processing.

6.341x is designed to provide both an in-depth and an intuitive understanding of the theory behind modern discrete-time signal processing systems and applications. The course begins with a review and extension of the basics of signal processing including a discussion of group delay and minimum-phase systems, and the use of discrete-time (DT) systems for processing of continuous-time (CT) signals. The course develops flow-graph and block diagram structures including lattice filters for implementing DT systems, and techniques for the design of DT filters. Parametric signal modeling and the efficient implementation of DT multirate and sampling rate conversion systems are discussed and developed. An in-depth development of the DFT and its computation as well as its use for spectral analysis and for filtering is presented. This component of the course includes a careful and insightful development of the relationship between the time-dependent Fourier transform and the use of filter banks for both spectral analysis and signal coding.

6.341x is organized around eleven units each typically consisting of a set of two to four topics. The source material for learning each topic includes suggested reading in the course text, clarifying notes, other related reading, and video excerpts and will include an interactive on-line discussion forum. The course text is the widely used text by Oppenheim and Schafer (third edition). The video segments are adapted from live video recordings of the MIT residential course. 

Each topic includes a set of automatically-graded exercises for self-assessment and to help in digesting and understanding the basics of the topic, and in some cases to preview topics. A typical unit in the course concludes with a set of more extensive problems to help in integrating the topics and developing a deeper understanding. Automatic grading of your answers to these problems as well as solutions will be provided.

6.341x and this freely-available version were developed through the support and encouragement of the MIT Department of Electrical Engineering and Computer Science, the MIT Office of Digital Learning, and the MIT Research Laboratory of Electronics.

This course can be cited as: Alan V. Oppenheim and Thomas A. Baran, 6.341x Discrete-Time Signal Processing, on edX, Summer 2016. https://www.edx.org/course/discrete-time-signal-processing-mitx-6-341x-1

This course examines how medicine is practiced cross-culturally, with particular emphasis on Western biomedicine. Students analyze medical practice as a cultural system, focusing on the human, as opposed to the biological, side of things. Also considered is how people in different cultures think of disease, health, body, and mind.

This course examines the growing importance of medicine in culture, economics and politics. It uses an historical approach to examine the changing patterns of disease, the causes of morbidity and mortality, the evolution of medical theory and practice, the development of hospitals and the medical profession, the rise of the biomedical research industry, and the ethics of health care in America.

Hoy en día prácticamente cualquiera con algo de responsabilidad en una organización tiene que hacer en algún momento una presentación eficaz con la que comunicar sus ideas o los resultados de su trabajo. Con este curso introductorio aprenderás las bases para hacer una presentación eficaz que llegue a tu público, conocerás qué imágenes y otros recursos de Internet podrás usar para ello sin infringir ninguna propiedad intelectual y aprenderás a utilizar las funciones básicas del programa Microsoft Powerpoint para realizar esta presentación

Unidades 

• Diseñando presentaciones eficaces
• Introducción a Powerpoint
• Añadiendo contenido a nuestra presentación​

En este curso aprenderás a diseñar, fabricar y programar tu propio robot (DYOR: Do Your Own Robot) con Arduino. Es una metodología que llevamos años implementando en asignaturas de robótica de la Universitat Politènica de València. Está principalmente enfocado a educadores en áreas de Tecnología e Informática, pero también para personas que quieren iniciarse en el mundo Maker.

El objetivo final del curso es disfrutéis aprendiendo en todo el proceso de diseño, fabricación y montaje del robot con actividades diversas, variadas y multidisciplinares. Por ello hemos preparado todos los contenidos necesarios que os permitirán fabricar un robot divertido, personalizable y de bajo coste partiendo desde cero y que vosotros podréis adaptar a vuestras necesidades. De forma orientativa, el coste de los materiales para fabricar el robot está en torno a los 65€, que correrán a cargo del alumno y que podrás comprar libremente donde más te interese.

El curso es idóneo para personas que quieran iniciarse en el mundo de la electrónica, fabricación digital y la robótica. Aprenderás a utilizar herramientas CAD (TinkerCAD), diseño electrónico (Fritzing) y programación por bloques de Arduino (Facilino) y apps Android (App Inventor2).

En el curso os explicamos divertidas actividades que podréis realizar con vuestros robots como generar emociones, reproducir melodías, controlar movimientos básicos, abrir/cerrar pinzas, seguir líneas, evitar obstáculos o controlar el robot remotamente desde un dispositivo móvil.

El curso está diseñado para sacar al estudiante de la fase romántica y teórica, despertándole acerca de la importancia de tomar iniciativas, riesgos y emprender acciones valientes que le permitan tomar ventaja de las diferentes situaciones que se presentan en su qué hacer. Presenta una serie de contenidos y consejos que lo convierten en una herramienta contundente para conseguir el éxito personal y/o en los negocios, permite reconocer los obstáculos, facilita decidir y actuar.

La estrategia se convierte en el elemento crucial que permite a personas, empresas, instituciones y países tomar ventaja de las situaciones que enfrenta, de los recursos con los que cuenta y para eso, el curso consigue el entendimiento preciso de la situación, la concepción original de la forma en que puede tomar la ventaja sobre competidores o adversarios y cómo generar el crecimiento sostenido a lo largo del tiempo, fortalece el liderazgo haciendo énfasis en el desarrollo del estratega, quien piensa y actúa en cualquier momento como tal, para quien su objetivo además de ser efectivo es triunfar en cada batalla librada a lo largo de su vida o en la empresa.

Permite analizar la forma en que toma decisiones y entiende sus limitantes, consigue que la visión sea de largo plazo y que se considere el tiempo y los recursos en general como escasos para orientarse siempre a su optimización, para ello, los modelos de estudio consideran siempre el asunto de la inversión y establece las diferencias que genera la orientación de la misma y su alineación con la estrategia primaria del negocio o del individuo, busca siempre la competitividad en su sentido más completo. Se trabaja sobre la originalidad y creatividad necesaria para conseguir que el factor sorpresa se consiga y genere ventaja. Partiendo del principio de que la estrategia se establece para el peor de los escenarios, todo el curso está basado en la realidad, en la que existe competencia y terrenos dificultosos para poder lograr los objetivos.

El curso “Diseño y desarrollo de recursos multimedia para la enseñanza virtual” está enfocado para que identifiques las principales características, utilidades y ventajas de los diferentes tipos de recursos multimedia que puedes construir para complementar o generar conocimiento; utilizarás tu creatividad al máximo al desarrollar presentaciones, actividades interactivas y videos educativos los cuales podrás integrar de forma eficiente a tus procesos de formación o bien como recurso de apoyo en tus clases presenciales.

El contenido se desarrolla en una serie de temas entrelazados y dosificados en 6 lecciones, en las que aprenderás de forma práctica y dinámica las diferentes metodologías, herramientas y técnicas de diseño para la elaboración de recursos educativos multimedia, poniendo en práctica las competencias digitales adquiridas construyendo recursos innovadores usando herramientas líderes en la industria de la producción multimedia como Articulate Storyline, Adobe Captivate, Camtasia, Adobe Spark entre otras.

Este curso forma parte del programa de MicroMasters “e-Learning: crea actividades y contenidos para la enseñanza virtual” diseñada con el propósito de desarrollar en los participantes  las habilidades y competencias necesarias para la implementación de entornos de aprendizaje innovadores apoyados por las TIC's. Al inscribirte en este programa de MicroMasters te daremos acceso a un área de descarga especial, en la cual encontrarás plantillas (predefinidas) de las principales herramientas presentadas en los cursos, guías de mejores prácticas y vídeos complementarios con entrevistas de reconocidos expertos a nivel internacional, que comparten su experiencia y conocimiento en el campo de la educación apoyada por tecnología, el diseño y producción de recursos multimedia.

Se conocerán los distintos sistemas de georreferenciación/navegación aplicados a dispositivos móviles, la estructura de los Sistemas de Información Geográfica (SIG) y su aplicabilidad a la gestión del territorio y se describirán los sistemas de comunicación existentes (GPRS/UMTS, internet), con el objeto de analizar las aplicaciones a la ingeniería y la gestión del territorio que proporciona la integración de estos tres sistemas en los dispositivos móviles.

Asimismo, se describirán los principales software de navegación y gestión de la información (SIG) existentes en el mercado para dispositivos móviles, incluyendo prácticas con algunos de ellos. Por último, se realizara una valoración de las distintas aplicaciones que pueden proporcionar los dispositivos móviles para la gestión del territorio, para la ingeniería, geografía, geología, ciencias medio ambientales…

Distributed algorithms are algorithms designed to run on multiple processors, without tight centralized control. In general, they are harder to design and harder to understand than single-processor sequential algorithms. Distributed algorithms are used in many practical systems, ranging from large computer networks to multiprocessor shared-memory systems. They also have a rich theory, which forms the subject matter for this course.

The core of the material will consist of basic distributed algorithms and impossibility results, as covered in Prof. Lynch's book Distributed Algorithms. This will be supplemented by some updated material on topics such as self-stabilization, wait-free computability, and failure detectors, and some new material on scalable shared-memory concurrent programming.

This course covers abstractions and implementation techniques for the design of distributed systems. Topics include: server design, network programming, naming, storage systems, security, and fault tolerance. The assigned readings for the course are from current literature. This course is worth 6 Engineering Design Points.