Courses tagged with "Information control" (1404)

The course aims at providing a fundamental understanding of the physics related to buildings and to propose an overview of the various issues that have to be adequately combined to offer the occupants a physical, functional and psychological well-being. Students will be guided through the different components, constraints and systems of a work of architecture. These will be examined both independently and in the manner in which they interact and affect one another.

Ever hang your head in shame after your Python program wasn't as fast as your friend's C program? Ever wish you could use objects without having to use Java? Join us for this fun introduction to C and C++! We will take you through a tour that will start with writing simple C programs, go deep into the caves of C memory manipulation, resurface with an introduction to using C++ classes, dive deeper into advanced C++ class use and the C++ Standard Template Libraries. We'll wrap up by teaching you some tricks of the trade that you may need for tech interviews.

We see this as a "C/C++ empowerment" course: we want you to come away understanding

1. why you would want to use C over another language (control over memory, probably for performance reasons),
2. why you would want to use C++ rather than C (objects), and
3. how to be useful in C and C++.

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 is a fast-paced introductory course to the C++ programming language. It is intended for those with little programming background, though prior programming experience will make it easier, and those with previous experience will still learn C++-specific constructs and concepts.

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 examines civic media in comparative, transnational and historical perspectives through the use of various theoretical tools, research approaches, and project design methods.

In this sophomore design course, you will be challenged with three design tasks: a first concerning water resources/treatment, a second concerning structural design, and a third focusing on the conceptual (re)design of a large system, Boston's Back Bay. The first two tasks require the design, fabrication and testing of hardware. Several laboratory experiments will be carried out and lectures will be presented to introduce students to the conceptual and experimental basis for design in both domains.

This course was based in large part on the Fall 2005 offering of 1.101, developed by Prof. Harold Hemond.

1.012 introduces students to the theory, tools, and techniques of engineering design and creative problem-solving, as well as design issues and practices in civil engineering. The course includes several design cases, with an emphasis on built facilities (e.g., buildings, bridges and roads). Project design explicitly concerns technical approaches as well as consideration of the existing built environment, natural environment, economic and social factors, and expected life span. A large design case is introduced, which is used in the subsequent specialty area design subjects (1.031, 1.041, 1.051) and the capstone design subject (1.013).

This course examines signals, systems and inference as unifying themes in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; group delay; state feedback and observers; probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization; least-mean square error estimation; Wiener filtering; hypothesis testing; detection; matched filters.

This course examines why democracy emerges and survives in some countries rather than in others; how political institutions affect economic development; and how American politics compares to that of other countries.

This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.

Visit the Seung Lab Web site.

This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.

Visit the Seung Lab Web site.

This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.

Visit the Seung Lab Web site.

6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.

Course Format

This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:

• A complete set of Lecture Videos by Prof. Guttag.
• Resources for each lecture video, such as Handouts, Slides, and Code Files.
• Recitation Videos by course TA's to review content and problem solving techniques.
• Homework problems with sample student solutions.
• Further Study collections of links to supplemental online content.
• Self-Assessment tools, including lecture questions with answers and unit quizzes with solutions, to assess your subject mastery.