Online courses directory (2511)

Everyday we are bombarded with the word "global" and encouraged to see globalization as the quintessential transformation of our age. But what exactly does "globalization" mean? How is it affecting the lives of people around the world, not only in economic, but social and cultural terms? How do contemporary changes compare with those from other historical periods? Are such changes positive, negative or simply inevitable? And, finally, how does the concept of the "global" itself shape our perceptions in ways that both help us understand the contemporary world and potentially distort it? This course begins by offering a brief overview of historical "world systems," including those centered in Asia as well as Europe. It explores the nature of contemporary transformations, including those in economics, media & information technologies, population flows, and consumer habits, not through abstractions but by focusing on the daily lives of people in various parts of the world. This course considers such topics as the day-to-day impact of computers in Silicon Valley and among Tibetan refugees; the dilemmas of factory workers in the US and rural Java; the attractions of Bombay cinema in Nigeria, the making of rap music in Japan, and the cultural complexities of immigrant life in France. This course seeks not only to understand the various forms globalization takes, but to understand its very different impacts world-wide.

This course is a core requirement for the Masters in Engineering program, designed to teach students about the roles of today's professional engineer and expose them to team-building skills through lectures, team workshops, and seminars. Topics include: written and oral communication, job placement skills, trends in the engineering and construction industry, risk analysis and risk management, managing public information, proposal preparation, project evaluation, project management, liability, professional ethics, and negotiation. The course draws on relevant large-scale projects to illustrate each component of the subject.

Material covered in this course includes the following topics:

• Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams
• Computation of phase diagrams
• Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions
• Applications to phase stability and properties of mixtures
• Computational modeling
• Interfaces

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium).

This class provides an introduction to the interactions between cells and the surfaces of biomaterials. The course covers: surface chemistry and physics of selected metals, polymers, and ceramics; surface characterization methodology; modification of biomaterials surfaces; quantitative assays of cell behavior in culture; biosensors and microarrays; bulk properties of implants; and acute and chronic response to implanted biomaterials. General topics include biosensors, drug delivery, and tissue engineering.

This course examines the ways in which people in ancient and contemporary societies have selected, evaluated, and used materials of nature, transforming them to objects of material culture. Some examples are: glass in ancient Egypt and Rome; sounds and colors of powerful metals in Mesoamerica; cloth and fiber technologies in the Inca empire. It also explores ideological and aesthetic criteria often influential in materials development. Laboratory/workshop sessions provide hands-on experience with materials discussed in class. This course complements 3.091.

In this course, we will lay the foundation for understanding how materials behave in nuclear systems. In particular, we will build on a solid base of nuclear material fundamentals in order to understand radiation damage and effects in fuels and structural materials. This course consists of a series of directed readings, lectures on video, problem sets, short research projects, and class discussions with worked examples. We will start with an overview of nuclear materials, where they are found in nuclear systems, and how they fail. We will then develop the formalism in crystallography as a common language for materials scientists everywhere. This will be followed by the development of phase diagrams from thermodynamics, which predict how binary alloy systems evolve towards equilibrium. Then effects of stress, defects, and kinetics will be introduced. These will all be tied together when developing theories about how radiation, particularly neutrons and heavy charged particles, interact with solid matter to produce defects and evolve microstructure. A few applications of radiation effects will then be treated with this newfound framework, including the change of material properties under irradiation, void swelling, embrittlement, loss of ductility, and the simulation of in-reactor irradiation (neutrons) with heavy ions.

This course is a required sophomore subject in the Department of Materials Science and Engineering, designed to be taken in conjunction with the core lecture subject 3.012 Fundamentals of Materials Science and Engineering. The laboratory subject combines experiments illustrating the principles of quantum mechanics, thermodynamics and structure with intensive oral and written technical communication practice. Specific topics include: experimental exploration of the connections between energetics, bonding and structure of materials, and application of these principles in instruments for materials characterization; demonstration of the wave-like nature of electrons; hands-on experience with techniques to quantify energy (DSC), bonding (XPS, AES, FTIR, UV/Vis and force spectroscopy), and degree of order (x-ray scattering) in condensed matter; and investigation of structural transitions and structure-property relationships through practical materials examples.

Professor Anne Mayes led the development and teaching of this course in prior years.

This course is focused on physical understanding of materials processing, and the scaling laws that govern process speed, volume, and material quality. In particular, this course will cover the transport of heat and matter as these topics apply to materials processing.

As its name implies, the 3.042 Materials Project Laboratory involves working with such operations as investment casting of metals, injection molding of polymers, and sintering of ceramics. After all the abstraction and theory in the lecture part of the DMSE curriculum, many students have found this hands-on experience with materials to be very fun stuff - several have said that 3.042/3.082 was their favorite DMSE subject. The lab is more than operating processing equipment, however. It is intended also to emulate professional practice in materials engineering project management, with aspects of design, analysis, teamwork, literature and patent searching, Web creation and oral presentation, and more.

This course provides techniques of effective presentation of mathematical material. Each section of this course is associated with a regular mathematics subject, and uses the material of that subject as a basis for written and oral presentations. The section presented here is on chaotic dynamical systems.

This graduate-level course is a continuation of Mathematical Methods for Engineers I (18.085). Topics include numerical methods; initial-value problems; network flows; and optimization.

Find out what solid-state physics has brought to Electromagnetism in the last 20 years. This course surveys the physics and mathematics of nanophotonics—electromagnetic waves in media structured on the scale of the wavelength.

Topics include computational methods combined with high-level algebraic techniques borrowed from solid-state quantum mechanics: linear algebra and eigensystems, group theory, Bloch's theorem and conservation laws, perturbation methods, and coupled-mode theories, to understand surprising optical phenomena from band gaps to slow light to nonlinear filters.

Note: An earlier version of this course was published on OCW as 18.325 Topics in Applied Mathematics: Mathematical Methods in Nanophotonics, Fall 2005.

This graduate level mathematics course covers decision theory, estimation, confidence intervals, and hypothesis testing. The course also introduces students to large sample theory. Other topics covered include asymptotic efficiency of estimates, exponential families, and sequential analysis.

This course provides students with decision theory, estimation, confidence intervals, and hypothesis testing. It introduces large sample theory, asymptotic efficiency of estimates, exponential families, and sequential analysis.

This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

This subject offers an interactive introduction to discrete mathematics oriented toward computer science and engineering. The subject coverage divides roughly into thirds:

1. Fundamental concepts of mathematics: Definitions, proofs, sets, functions, relations.
2. Discrete structures: graphs, state machines, modular arithmetic, counting.
3. Discrete probability theory.

On completion of 6.042J, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in computer science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.

Interactive site components can be found on the Unit pages in the left-hand navigational bar, starting with Unit 1: Proofs.

This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis.

Users may find additional or updated materials at Professor Carter's 3.016 course Web site.

Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis.

You can read more about Prof. Rigollet's work and courses on his website.

This International Study Tour went to New Zealand during the first half of the 2016 Spring semester and travel during the Sloan Innovation Period. International Study Tours provide students with a course credit opportunity to identify and address issues about which they feel particularly passionate. After classroom sessions featuring faculty, industry, and cultural experts, students embark on site visits to their destination of choice, meeting with industry and government leaders, as well as local alumni. Through these visits, students are able to build on the preparatory course work with an in-depth exploration of industries, companies, and countries they have visited.

This course fulfills the Sloan Innovation Period (SIP) elective requirement. SIP occurs at the midpoint of each semester providing students with an intensive week of experiential leadership learning, as well as exposure to groundbreaking faculty work. It allows students to engage in intellectual exploration outside the classroom. SIP degree requirements include core courses in ethics and leadership as well as electives.