Courses tagged with "Nutrition" (421)

本課程教授BIM技術的基礎知識，並以貼近實務之工程案例為教學範例，教授BIM塑模之基礎觀念與操作邏輯，並讓學生能實際應用BIM工具於案例實作中。

本課程教授BIM技術應用的基本知識及發展潛力，重點放在如何應用BIM資訊模型於實務工程中，包括設計衝突之檢討、工程數量之估算、工程進度之管理等應用。

本課程有兩大課程目標： 1. 使同學了解如何以搜尋達成人工智慧 2. 使同學能將相關技術應用到自己的問題上

Learn various methods of analysis including: unsupervised clustering, gene-set enrichment analyses, Bayesian integration, network visualization, and supervised machine learning applications to LINCS data and other relevant Big Data from high content molecular and phenotype profiling of human cells.

This is the second course in a two-part series on bioinformatics algorithms, covering the following topics: evolutionary tree reconstruction, applications of combinatorial pattern matching for read mapping, gene regulatory analysis, protein classification, computational proteomics, and computational aspects of human genetics.

讲授C++语言中和面向对象有关的概念和语法，如类和对象、运算符重载、继承和多态、类模板和算法模板、标准模板库等。目标是使得学生能够用C++语言，以面向对象的方法编写可维护性、可扩充性好的，较大规模的程序，初步领会面向对象程序设计方法的优势所在。

Learn how to use the cloud and write programs for data analytics.

Learn core distributed computing concepts that underlie today’s and tomorrow’s cloud computing systems.

Learn core distributed computing concepts that underlie today’s and tomorrow’s cloud computing systems.

The network is what makes the cloud. The cloud’s key capabilities—the ability to share infrastructure, the ability to move and scale applications across servers, massive parallelism, virtualization, and worldwide connectivity—are all rooted in the network. Learn how it all works!

Learn how to take scattered data and organize it into groups for use in many applications, such as market analysis and biomedical data analysis, or as a pre-processing step for many data mining tasks.

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer.

Designed to equip students with the fundamental elements of programming and data abstraction using Java.

Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation.

Week 1: A first simple neuron model

Week 2:  Hodgkin-Huxley models and biophysical modeling

Week 3: Two-dimensional models and phase plane analysis

Week 4: Two-dimensional models (cont.)/ Dendrites

Week 5: Variability of spike trains and the neural code

Week 6: Noise models, noisy neurons and coding

Week 7: Estimating neuron models for coding and decoding

Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.

This intermediate computer programming course uncovers how to code long-lasting software using highly-productive Agile techniques to develop Software as a Service (SaaS) using Ruby on Rails. You will understand the new challenges and opportunities of SaaS versus shrink-wrapped software and learn to apply fundamental Rails programming techniques to the design, development, testing, and public cloud deployment of an Software as a Service (SaaS) application

Using best-of-breed tools that support modern development techniques including Behavior-Driven design, user stories, Test-Driven Development, velocity, and pair programming, learners will discover how modern programming language features in Ruby on Rails can improve productivity and code maintainability. 

Weekly coding projects and quizzes will be part of the learning experience in this SaaS course. Those who successfully complete the assignments and earn a passing grade can get a verified certificate from BerkeleyX. The videos and homework assignments have been updated to use Ruby 2, Rails 4 and RSpec 3. The new class also includes embedded live chat with Teaching Assistants and other students and remote pair programming with other students.

In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications. 

The class will consist of lecture videos, which are broken into small pieces, usually between 4 and 8 minutes each. After each lecture piece, we will ask you a “quick question” to assess your understanding of the material. There will also be a recitation, in which one of the teaching assistants will go over the methods introduced with a new example and data set. Each week will have a homework assignment that involves working in R or LibreOffice with various data sets. (R is a free statistical and computing software environment we’ll use in the course. See the Software FAQ below for more info). In the middle of the class, we will run an analytics competition, and at the end of the class there will be a final exam, which will be similar to the homework assignments.

How do you design a mobile app that truly changes people's lives? How can you understand how a new service is being used, both quantitatively and qualitatively? How can you use all of the rich sensing and I/O capabilities of mobile devices to create experiences that go far beyond what's possible on a traditional computer?

Mobile devices are changing the ways that we interact with each other and information in the world. This course will take you from a domain of interest, through generative research, design, usability, implementation and field evaluation of a novel mobile experience. You'll finish the course with a working, field-tested application suitable for release in the app store as well as a deep understanding of human interaction with mobile devices and services.

Based on a popular MIT class that has been taught since 2006 by Frank Bentley of Yahoo Labs and Ed Barrett, a Senior Lecturer at MIT, this course will explore what makes mobile devices unique. A primary focus will be on studying existing behavior and using key findings for design. While writing the code for an app is a part of the class, the majority of the topics will cover designing and evaluating a unique mobile experience. Along the way, you will have opportunities to share your work with other students from around the world! Java experience (or Objective C for iOS users) and a smartphone are required.

All required readings are available within the courseware, courtesy of The MIT Press. A print version of the course textbook, Building Mobile Experiences, is also available for purchase. The MIT Press is offering enrolled students a special 30% discount on books ordered directly through the publisher’s website. To take advantage of this offer, please use promotion code BME30 at The MIT Press site.

This course teaches the concepts and computational methods in the exciting interdisciplinary field of bioinformatics and their applications in life sciences. The lectures are taught in both Mandarin Chinese and English with slides in English. 生物信息学是一门新兴的生命科学与计算科学的前沿交叉学科。本课程讲授生物信息学主要概念和方法，以及如何应用生物信息学手段解决生命科学问题。本课程同时提供中文普通话授课和英文授课两个版本，以及英文幻灯片。