Foundations subject in modern software development techniques for engineering and information technology. Covers the design and development of component-based software (using C# and .NET); data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications.

" This course is an introduction to software engineering, using the Java™ programming language. It covers concepts useful to 6.005. Students will learn the fundamentals of Java. The focus is on developing high quality, working software that solves real problems. The course is designed for students with some programming experience, but if you have none and are motivated you will do fine. Students who have taken 6.005 should not take this course. Each class is composed of one hour of lecture and one hour of assisted lab work. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month."

This course is an introduction to Java programming and software engineering. It is designed for those who have little or no programming experience in Java and covers concepts useful to 6.005. The focus is on developing high quality, working software that solves real problems. Students will learn the fundamentals of Java, and how to use 3rd party libraries to get more done with less work. Each session includes one hour of lecture and one hour of assisted lab work. Short labs are assigned with each lecture. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

A basic tutorial on using classes and objects in Java, plus some discussion of what classes and objects actually are. This tutorial focuses on classes containing only data; next time I'll look at "methods".

Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical foundations of the concept will be followed by a discussion of two or three relevant research papers in computer vision, medical and biological imaging, that use the concept in different ways. We will aim to understand the fundamental techniques and to recognize situations in which these techniques promise to improve the quality of the analysis.

Many of the inanimate objects around you probably seem perfectly still. But look deep into the atomic structure of any of them, and you’ll see a world in constant flux — with stretching, contracting, springing, jittering, drifting atoms everywhere. Ran Tivony describes how and why molecular movement occurs and investigates if it might ever stop.