17.869 Political Science Scope and Methods (MIT)
This course is designed to provide an introduction to a variety of empirical research methods used by political scientists. The primary aims of the course are to make you a more sophisticated consumer of diverse empirical research and to allow you to conduct sophisticated independent work in your junior and senior years. This is not a course in data analysis. Rather, it is a course on how to approach political science research.
14.124 Microeconomic Theory IV (MIT)
The topic of the class is information economics. The purpose is to give an introduction to some of the main subjects in this field: risk sharing, moral hazard, adverse selection (signaling, screening), mechanism design, decision making under uncertainty. These subjects (and others) will be treated in more depth in the advanced theory courses on Contract Theory.
15.020 Competition in Telecommunications (MIT)
Competition in Telecommunications provides an introduction to the economics, business strategies, and technology of telecommunications markets. This includes markets for wireless communications, local and long-distance services, and customer equipment. The convergence of computers, cable TV and telecommunications and the competitive emergence of the Internet are covered in depth. A number of speakers from leading companies in the industry will give course lectures.
15.066J System Optimization and Analysis for Manufacturing (MIT)
One objective of 15.066J is to introduce modeling, optimization and simulation, as it applies to the study and analysis of manufacturing systems for decision support. The introduction of optimization models and algorithms provide a framework to think about a wide range of issues that arise in manufacturing systems. The second objective is to expose students to a wide range of applications for these methods and models, and to integrate this material with their introduction to operations managemen
15.075 Applied Statistics (MIT)
This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra.
We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Pro
15.328 Team Project (MIT)
The Team Project has the goals of (1) developing teamwork and leadership skills and (2) learning from the analysis of a change initiative in a real-world company using concepts from other core courses. This class has no regular class schedule or weekly readings. Almost everything is oriented around your team and your project, with only a few deadlines. Each team is responsible for analyzing a recent, ongoing, or anticipated initiative at a real company. Examples might be a strategic reorien
15.874 System Dynamics for Business Policy (MIT)
15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using
15.057 Systems Optimization (MIT)
Managers and engineers are constantly attempting to optimize, particularly in the design and operation of complex systems. This course is an application-oriented introduction to (systems) optimization. It seeks to:
Motivate the use of optimization models to support managers and engineers in a wide variety of decision making situations;
Show how several application domains (industries) use optimization;
Introduce optimization modeling and solution techniques (including linear, non-linear, intege
15.062 Data Mining (MIT)
Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. Data mining is a rapidly growing field that
6.844 Computability Theory of and with Scheme (MIT)
6.844 is a graduate introduction to programming theory, logic of programming, and computability, with the programming language Scheme used to crystallize computability constructions and as an object of study itself. Topics covered include: programming and computability theory based on a term-rewriting, "substitution" model of computation by Scheme programs with side-effects; computation as algebraic manipulation: Scheme evaluation as algebraic manipulation and term rewriting theory; paradoxes fr
21L.460 Medieval Literature: Medieval Women Writers (MIT)
This survey provides a general introduction to medieval European literature (from Late Antiquity to the Fifteenth Century) from the perspective of women writers from a variety of cultures, social backgrounds, and historical timeperiods. Though much of the class will be devoted to exploring the evolution of a new literary tradition by and for women from its earliest emergence in the West, wider historical and cultural movements will also be addressed: the Fall of the Roman Empire, the growth
2.997 Decision Making in Large Scale Systems (MIT)
This course is an introduction to the theory and application of large-scale dynamic programming. Topics include Markov decision processes, dynamic programming algorithms, simulation-based algorithms, theory and algorithms for value function approximation, and policy search methods. The course examines games and applications in areas such as dynamic resource allocation, finance and queueing networks.
17.874 Quantitative Research Methods: Multivariate (MIT)
This course is the second semester in the statistics sequence for political science and public policy offered in the Political Science Department at MIT. The intellectual thrust of the course is a presentation of statistical models for estimating causal effects of variables. The model of an effect is a conditional mean (though we might imagine other effect). The notion of causality is the effect of one variable on another holding all else constant.
18.443 Statistics for Applications (MIT)
This course provides a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. The course topics include hypothesis testing and estimation. It also includes confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, and correlation.
6.837 Computer Graphics (MIT)
6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.
From Experimental Physics to Internet Entrepreneurship: One Scientist’s Journey
Few better personify the vitality and ambition fueling China’s economic surge than Charles C-Y Zhang. In this energetic and revelatory talk, Zhang relates his personal evolution from MIT physicist to leading Chinese entrepreneur.
An industrious student from a poor family, Zhang was one of the fortunate few in hi
18.125 Measure and Integration (MIT)
This graduate-level course covers Lebesgue's integration theory with applications to analysis, including an introduction to convolution and the Fourier transform.
1.017 Computing and Data Analysis for Environmental Applications (MIT)
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-wo
Introduction to OO Programming in Java - Classes and arithmetic
This visual aid forms part of the "Classes and arithmetic" topic in the Introduction to OO Programming in Java module.
18.413 Error-Correcting Codes Laboratory (MIT)
This course introduces students to iterative decoding algorithms and the codes to which they are applied, including Turbo Codes, Low-Density Parity-Check Codes, and Serially-Concatenated Codes. The course will begin with an introduction to the fundamental problems of Coding Theory and their mathematical formulations. This will be followed by a study of Belief Propagation--the probabilistic heuristic which underlies iterative decoding algorithms. Belief Propagation will then be applied to the dec
