This subject examines the ways in which we read. It introduces some important strategies for engaging with literary texts developed in the twentieth century, paying special attention to poststructuralist theories and their legacy. The course is organized around specific theoretical paradigms. In general, we will: (1) work through the selected readings in order to see how they construe what literary interpretation is; (2) locate the limits of each particular approach; and (3) trace the emergence of subsequent theoretical paradigms as responses to what came before.

This is an accelerated introduction to MATLAB® and its popular toolboxes. Lectures are interactive, with students conducting sample MATLAB problems in real time. The course includes problem-based MATLAB assignments. Students must provide their own laptop and software. This is great preparation for classes that use MATLAB.

This course was offered as a non-credit program during the Independent Activities Period (IAP), January 2008. A more recent version is available as course 18.S997 Introduction To MATLAB Programming, including video lectures.
The course, intended for students with no programming experience, provides the foundations of programming in MATLAB®. Variables, arrays, conditional statements, loops, functions, and plots are explained. At the end of the course, students should be able to use MATLAB in their own work, and be prepared to deepen their MATLAB programming skills and tackle other languages for computing, such as Java, C++, or Python.
The course mostly follows the official MATLAB Manual, available from The MathWorks. We will cover material from chapters 2-5.

This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction. It includes formulation of learning problems and concepts of representation, over-fitting, and generalization. These concepts are exercised in supervised learning and reinforcement learning, with applications to images and to temporal sequences.
This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling.

This course provides ways to analyze manufacturing systems in terms of material flow and storage, information flow, capacities, and times and durations of events. Fundamental topics include probability, inventory and queuing models, optimization, and linear and dynamic systems. Factory planning and scheduling topics include flow planning, bottleneck characterization, buffer and batch-size analysis, and dynamic behavior of production systems.

This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms.

This course provides a critical analysis of mass media in our culture. Various types of media such as books, films, video games, and online interactions will be discussed and reviewed. This course will also evaluate how information and ideas travel between people on a large scale.

Introduction to Media Studies is designed for students who have grown up in a rapidly changing global multimedia environment and want to become more literate and critical consumers and producers of culture. Through an interdisciplinary comparative and historical lens, the course defines “media” broadly as including oral, print, theatrical, photographic, broadcast, cinematic, and digital cultural forms and practices. The course looks at the nature of mediated communication, the functions of media, the history of transformations in media and the institutions that help define media’s place in society.
Over the course of the semester we explore different theoretical perspectives on the role and power of media in society in influencing our social values, political beliefs, identities and behaviors. Students also have the opportunity to analyze specific media texts (such as films and television shows) and explore the meaning of the changes that occur when a particular narrative is adapted into different media forms. We look at the ways in which the politics of class, gender and race influence both the production and reception of media. To represent different perspectives on media, several guest speakers also present lectures. Through the readings, lectures, and discussions as well as their own writing and oral presentations, students have multiple opportunities to engage with critical debates in the field as well as explore the role of media in their own lives.

Introduction to Media Studies is designed for students who have grown up in a rapidly changing global multimedia environment and want to become more literate and critical consumers and producers of media. Through an interdisciplinary comparative and historical lens, the course defines “media” broadly as including oral, print, performance, photographic, broadcast, cinematic, and digital cultural forms and practices. The course looks at the nature of mediated communication, the functions of media, the history of transformations in media and the institutions that help define media’s place in society. This year’s course will focus on issues of network culture and media convergence, addressing such subjects as Intellectual Property, peer2peer authoring, blogging, and game modification.

This course provides a basic introduction to metric spaces. It covers metrics, open and closed sets, continuous functions (in the topological sense), function spaces, completeness, and compactness.

This subject provides an introduction to modeling and simulation, covering continuum methods, atomistic and molecular simulation, and quantum mechanics. Hands-on training is provided in the fundamentals and applications of these methods to key engineering problems. The lectures provide exposure to areas of application based on the scientific exploitation of the power of computation. We use web based applets for simulations, thus extensive programming skills are not required.

Through a progressive series of composition projects, students investigate the sonic organization of musical works and performances, focusing on fundamental questions of unity and variety. Aesthetic issues are considered in the pragmatic context of the instructions that composers provide to achieve a desired musical result, whether these instructions are notated in prose, as graphic images, or in symbolic notation. No formal training is required. Weekly listening, reading, and composition assignments draw on a broad range of musical styles and intellectual traditions, from various cultures and historical periods.

Traditionally, progress in electronics has been driven by miniaturization. But as electronic devices approach the molecular scale, classical models for device behavior must be abandoned. To prepare for the next generation of electronic devices, this class teaches the theory of current, voltage and resistance from atoms up. To describe electrons at the nanoscale, we will begin with an introduction to the principles of quantum mechanics, including quantization, the wave-particle duality, wavefunctions and Schrödinger’s equation. Then we will consider the electronic properties of molecules, carbon nanotubes and crystals, including energy band formation and the origin of metals, insulators and semiconductors. Electron conduction will be taught beginning with ballistic transport and concluding with a derivation of Ohm’s law. We will then compare ballistic to bulk MOSFETs. The class will conclude with a discussion of possible fundamental limits to computation.

This course provides an introduction to complex networks and their structure and function, with examples from engineering, applied mathematics, and social sciences. Topics include spectral graph theory, notions of centrality, random graph models, contagion phenomena, cascades and diffusion, and opinion dynamics.

This course introduces quantitative approaches to understanding brain and cognitive functions. Topics include mathematical description of neurons, the response of neurons to sensory stimuli, simple neuronal networks, statistical inference and decision making. It also covers foundational quantitative tools of data analysis in neuroscience: correlation, convolution, spectral analysis, principal components analysis, and mathematical concepts including simple differential equations and linear algebra.

This course explores the organization of synaptic connectivity as the basis of neural computation and learning. Perceptrons and dynamical theories of recurrent networks including amplifiers, attractors, and hybrid computation are covered. Additional topics include backpropagation and Hebbian learning, as well as models of perception, motor control, memory, and neural development.

This subject will be an intensive introduction to neuroanatomy, involving lectures, demonstrations, and hands-on laboratories, including a brain dissection. The course will not assume any prior knowledge of neuroanatomy, though some general knowledge of brain structures will be helpful.

The course will span modern neuroscience from molecular neurobiology to perception and cognition, including the following major topics: anatomy and development of the brain; cell biology of neurons and glia; ion channels and electrical signaling; synaptic transmission, integration, and chemical systems of the brain; sensory systems, from transduction to perception; motor systems; and higher brain functions dealing with memory, language, and affective disorders.

This course is an introduction to the mammalian nervous system, with emphasis on the structure and function of the human brain. Topics include the function of nerve cells, sensory systems, control of movement, learning and memory, and diseases of the brain.

This course provides an introduction to nuclear science and its engineering applications. It describes basic nuclear models, radioactivity, nuclear reactions, and kinematics; covers the interaction of ionizing radiation with matter, with an emphasis on radiation detection, radiation shielding, and radiation effects on human health; and presents energy systems based on fission and fusion nuclear reactions, as well as industrial and medical applications of nuclear science.