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.

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.

From satellites gathering imagery from hundreds of miles above the Earth's surface to aerial systems mounted with lasers capable of generating 3D maps with centimeter accuracy, we're gathering more data about our Earth from above than ever before. This course will help you make sense of these complex and exciting datasets. Whether your interest is in natural disasters, environmental assessment, or national security, we'll give you the tools, methods, and techniques to extract actionable and meaningful information from these data. This course will help you understand that an image is more than just a pretty picture.

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.

Upon completion of this course, students will be able to: develop and research a topic of global significance; recognize authors‰ŰŞ arguments and the political, social and economic motivations behind their work; demonstrate the ability to locate, interpret and cite the relevant and appropriate information resources on a topic; and, demonstrate an understanding of the information research process.Login: guest_oclPassword: ocl

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 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 is developed to help you understand how information technology can be used as part of an organizationŐs overall strategy.

Technical Project Management in Living and Geometric Order demonstrates that even the best-laid project plans can be undone by new technologies, financial upheavals, or resource scarcity, to name just a few disruptors. It encourages project managers to focus on learning throughout a project, with the understanding that what they learn could necessitate major changes in midstream. This adaptive, flexible, living-order approach is inspired by Lean in construction projects and Agile in software development. Technical Project Management in Living and Geometric Order explains how today’s projects unfold in dynamic environments in response to unexpected events. With its practical tips, detailed graphics, links to additional resources, and interviews with engineering professionals, it’s an accessible introduction to the living order for aspiring project managers.

This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system.

This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system.

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.

The web gives us many strategies and tactics and tools, which, properly used, can get students closer to the truth of a statement or image within seconds. For some reason we have decided not to teach students these specific techniques. As many people have noted, the web is both the largest propaganda machine ever created and the most amazing fact-checking tool ever invented. But if we haven't taught our students those capabilities is it any surprise that propaganda is winning?

This is an unabashedly practical guide for the student fact-checker. It supplements generic information literacy with the specific web-based techniques that can get you closer to the truth on the web more quickly.

Diversity begets creativity - in this seminar we tap the amazing power of swarm creativity on the Web by studying and working together as Collaborative Innovation Networks (COINs). As interdisciplinary teams of MIT management, SCAD design, University of Cologne informatics, and Aalto University software engineering students we will explore how to discover latest trends on the Web, and how to make them succeed in online social networks. We study a wide range of methods for predictive analytics (coolhunting) and online social marketing (coolfarming), mostly based on social network analysis and the emerging science of collaboration. Students will also learn to use our own unique MIT-developed Condor tool for Web mining, social network analysis, and trend prediction.