Courses tagged with "Information control" (1404)

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have?

An introduction to computational theories of human cognition. Emphasizes questions of inductive learning and inference, and the representation of knowledge. Project required for graduate credit. This class is suitable for intermediate to advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields.

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have?

This class introduces design as a computational enterprise in which rules are developed to compose and describe architectural and other designs. The class covers topics such as shapes, shape arithmetic, symmetry, spatial relations, shape computations, and shape grammars. It focuses on the application of shape grammars in creative design, and teaches shape grammar fundamentals through in-class, hands-on exercises with abstract shape grammars. The class discusses issues related to practical applications of shape grammars.

This course serves as an introduction to computational techniques arising in aerospace engineering. Applications are drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques include: numerical integration of systems of ordinary differential equations; finite-difference, finite-volume, and finite-element discretization of partial differential equations; numerical linear algebra; eigenvalue problems; and optimization with constraints.

This course provides an introduction to numerical methods and computational techniques arising in aerospace engineering. Applications are drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques covered include numerical integration of systems of ordinary differential equations; numerical discretization of partial differential equations; and probabilistic methods for quantifying the impact of variability. Specific emphasis is given to finite volume methods in fluid mechanics, and finite element methods in structural mechanics.

Acknowledgement: Prof. David Darmofal taught this course in prior years, and created some of the materials found in this OCW site.

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

This course immerses students in the process of building and testing their own digital and board games in order to better understand how we learn from games. We explore the design and use of games in the classroom in addition to research and development issues associated with computer–based (desktop and handheld) and non–computer–based media. In developing their own games, students examine what and how people learn from them (including field testing of products), as well as how games can be implemented in educational settings.

This course provides introduction to computer graphics algorithms, software and hardware. Topics include: ray tracing, the graphics pipeline, transformations, texture mapping, shadows, sampling, global illumination, splines, animation and color. This course offers 6 Engineering Design Points in MIT's EECS program.

This course analyzes issues associated with the implementation of higher-level programming languages. Topics covered include: fundamental concepts, functions, and structures of compilers, the interaction of theory and practice, and using tools in building software. The course includes a multi-person project on compiler design and implementation.

This course covers topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, virtual memory, and threads; networks; atomicity and coordination of parallel activities; recovery and reliability; privacy, security, and encryption; and impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrasts. Two design projects are required, and students engage in extensive written communication exercises.

This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for the analysis of quantitative data in science and engineering. The MATLAB® programming language is used to perform virtual experiments and to analyze real-world data sets, many downloaded from the web. Programming applications include display and assessment of data sets, investigation of hypotheses, and identification of possible casual relationships between variables. This is the first semester that two courses, Computing and Data Analysis for Environmental Applications (1.017) and Uncertainty in Engineering (1.010), are being jointly offered and taught as a single course.

Do you like teaching, but find yourself frustrated by how little students seem to learn? Would you like to try teaching, but are nervous about whether you will be any good at it? Are you interested in new research on science education? Research in science education shows that the greatest obstacle to student learning is the failure to identify and confront the misconceptions with which the students enter the class or those that they acquire during their studies. This weekly seminar course focuses on developing the participants' ability to uncover and confront student misconceptions and to foster student understanding and retention of key concepts. Participants read primary literature on science education, uncover basic concepts often overlooked when teaching biology, and lead a small weekly discussion session for students currently enrolled in introductory biology classes.

The instructor for this course, Dr. Kosinski-Collins, is a member of the HHMI Education Group.

The United States Congress is the most open of the national branches of government, and therefore the most closely studied. This course aims to find ways to deal with the vast array of information we have about Congress by asking two basic questions: What does Congress do (and why), and what are the various ways of studying congressional behavior? This course focuses on both the internal processes of the House and Senate, and on the place of Congress in the American political system.

This course analyzes the development of the United States Congress by focusing on the competing theoretical lenses through which legislatures have been studied. In particular, it compares sociological and economic models of legislative behavior, applying those models to floor decision-making, committee behavior, political parties, relations with other branches of the Federal government, and elections. Graduate students are expected to pursue the subject in greater depth through reading and individual research.

This course examines American constitutional law in historical and modern context. It focuses closely on the constitutional text and Supreme Court case law. It explores the allocation of decision-making authority among government institutions, including the distribution of power across the branches of the federal government and between the federal and state governments. The course also examines the guarantees of individual rights and liberties stemming from the due process, equal protection, and other clauses in the Bill of Rights and post Civil War amendments.

Acknowledgments

Professor Warshaw would like to acknowledge the training in Constitutional Law he received from Gary J. Jacobsohn, Kathleen Sullivan, and Norman Spaulding.