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 Schrĺ_dinger'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.

As the volume of information grows in databases, libraries and on the Internet, information literacy skills are key to being able to find and manage information effectively in a complex society. Information literacy is about recognizing when information is needed, and locating, critically evaluating, using and presenting the information to suit a specific purpose. These skills are increasingly in demand by individuals and employers alike. In developing and assessing your information literacy skills, you will learn to use and adapt your skill confidently and effectively in different situations and contexts. This unit is designed to be studied for 1 hour per week over 50 weeks.

Skills in information technology (IT) cover a broad range, from using software packages effectively to developing a critical understanding of the strengths and weaknesses of IT solutions. Developing your IT skills means planning your work, practising your skills, seeking feedback from others and reviewing your approach. In developing and assessing your IT skills, you will learn to use and adapt your skills effectively and confidently in different situations and contexts. This unit is designed to be studied for 1 hour per week over 50 weeks

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 class introduces elementary programming concepts including variable types, data structures, and flow control. After an introduction to linear algebra and probability, it covers numerical methods relevant to mechanical engineering, including approximation (interpolation, least squares and statistical regression), integration, solution of linear and nonlinear equations, ordinary differential equations, and deterministic and probabilistic approaches. Examples are drawn from mechanical engineering disciplines, in particular from robotics, dynamics, and structural analysis. Assignments require MATLAB programming.

This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language software project.

The course purpose is to provide the substance and skill necessary to make sound business decisions relating to information systems, and to work with senior line managers in the resolution of issues and problems in this area. Categories of issues which will be addressed in the course include: How do IT and its various manifestations in business, such as the Internet, affect current and future competitiveness? How do we align business strategy and plans with IT strategy and IT plans? How can we engage executives in learning and leading IT-related change? How do we implement new systems, change work behavior, manage projects? How should we organize and govern IT in an organization.

"This course provides a thorough introduction to the C programming language, the workhorse of the UNIX operating system and lingua franca of embedded processors and micro-controllers. The first two weeks will cover basic syntax and grammar, and expose students to practical programming techniques. The remaining lectures will focus on more advanced concepts, such as dynamic memory allocation, concurrency and synchronization, UNIX signals and process control, library development and usage. Daily programming Assignments and Labs and weekly laboratory exercises are required. Knowledge of C is highly marketable for summer internships, UROPs, and full-time positions in software and embedded systems development."

Principles of Computer System Design: An Introduction is published in two parts. Part I, containing chapters 1-6, is a traditional printed textbook published by Morgan Kaufman, an imprint of Elsevier. Part II, containing chapters 7-11, is available here as an open educational resource. This textbook, an introduction to the principles and abstractions used in the design of computer systems, is an outgrowth of notes written for 6.033 Computer System Engineering over a period of 40-plus years. Individual chapters are also used in other EECS subjects. There is also a Web site for the current 6.033 class with a lecture schedule that includes daily Assignments and Labs, lecture notes, and lecture slides. The 6.033 class Web site also contains a thirteen-year archive of class Assignments and Labs, design projects, and quizzes. Technical Requirements: Special software is required to use some of the files in this resource: .key, .ppt, and .zip.

Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.

The Internet, like the telephone system which preceded it, depends for its existence on communications networks. This unit examines these networks as the means of interconnecting devices so that two-way communication is possible. Examining protocols like HTTP, TCP/IP and ATM as well as the OSI reference model, it provides and overview of the topic for learners who have significant prior knowledge of the subject.

This course is an introduction to quantum computational complexity theory, the study of the fundamental capabilities and limitations of quantum computers. Topics include complexity classes, lower bounds, communication complexity, proofs, advice, and interactive proof systems in the quantum world. The objective is to bring students to the research frontier.

This course examines quantum computation and quantum information. Topics include quantum circuits, quantum Fourier transform and search algorithms, physical implementations, the quantum operations formalism, quantum error correction, stabilizer and Calderbank-Shor-Steans codes, fault tolerant quantum computation, quantum data compression, entanglement, and proof of the security of quantum cryptography. Prior knowledge of quantum mechanics and basic information theory is required.

Advanced seminar extends computer and analytic skills developed in the other subjects in this sequence into a research environment. Students present a structured discussion of a journal article representative of current research in Planning Decision Support Systems, and complete an approved short research project. Suggested research projects include topics related to ongoing research projects of the Computer Resource Laboratory. Seminar participants and invited guests will lead critical discussions of current literature and ongoing research. Each student will be responsible for identifying, reviewing, and presenting one structured discussion of articles from the current literature that are relevant to their research topic. The remaining time will be spent working on individual projects or thesis proposals. This fall, the seminar will focus on the following core issues that underlie most implementations of urban information systems and decision support tools: the sustainable acquisition and representation of urban knowledge; the emergent technological infrastructure for supporting metropolitan decision-making; and the innovative organizational and institutional arrangements that can take advantage of modern urban information systems.

The Software Tools for Academics and Researchers (STAR) program at MIT seeks to bridge the divide between scientific research and the classroom. Understanding and applying research methods in the classroom setting can be challenging due to time constraints and the need for advanced equipment and facilities. The multidisciplinary STAR team collaborates with faculty from MIT and other educational institutions to design software exploring core scientific research concepts. The goal of STAR is to develop innovative and intuitive teaching tools for classroom use. All of the STAR educational tools are freely available. To complement the educational software, the STAR website contains curriculum components/modules which can facilitate the use of STAR educational tools in a variety of educational settings. Students, teachers, and professors should feel welcome to download software and curriculum modules for their own use. Online Publication

" This class teaches the fundamentals of signals and information theory with emphasis on modeling audio/visual messages and physiologically derived signals, and the human source or recipient. Topics include linear systems, difference equations, Z-transforms, sampling and sampling rate conversion, convolution, filtering, modulation, Fourier analysis, entropy, noise, and Shannon's fundamental theorems. Additional topics may include data compression, filter design, and feature detection. The undergraduate subject MAS.160 meets with the two half-semester graduate subjects MAS.510 and MAS.511, but Assignments and Labs differ."

This course covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.

6.301 is a course in analog circuit analysis and design. We cover the tools and methods necessary for the creative design of useful circuits using active devices. The class stresses insight and intuition, applied to the design of transistor circuits and the estimation of their performance. We concentrate on circuits using the bipolar junction transistor, but the techniques that we study can be equally applied to circuits using JFETs, MOSFETs, MESFETs, future exotic devices, or even vacuum tubes.

Extends the computing and geographic information systems (GIS) skills developed in 11.520 to include spatial data management in client/server environments and advanced GIS techniques. First half covers the content of 11.523, introducing database management concepts, SQL (Structured Query Language), and enterprise-class database management software. Second half explores advanced features and the customization features of GIS software that perform analyses for decision support that go beyond basic thematic mapping. Includes the half-semester GIS project of 11.524 that studies a real-world planning issue.

This course examines human-computer interaction in the context of graphical user interfaces. The course covers human capabilities, design principles, prototyping techniques, evaluation techniques, and the implementation of graphical user interfaces. Deliverables include short programming assignments and a semester-long group project. Students taking the graduate version also have readings from current literature and additional assignments.