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MIT

Fundamentals of Systems Engineering

General introduction to systems engineering using both the classical V-model and the new Meta approach. Topics include stakeholder analysis, requirements definition, system architecture and concept generation, trade-space exploration and concept selection, design definition and optimization, system integration and interface management, system safety, verification and validation, and commissioning and operations. Discusses the trade-offs between performance, lifecycle cost and system operability. Readings based on systems engineering standards and papers. Students apply the concepts of systems engineering to a cyber-electro-mechanical system, which is subsequently entered into a design competition. Students will prepare a PDR (Preliminary Design Review)-level design intended for the Cansat Competition.This year’s class will be taught in the form of a Small-Private-Online-Course (SPOC) and offered simultaneously to students at MIT under number 16.842 and Ecole Polytechnique Fédérale de Lausanne (EPFL) as ENG-421.

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4223

Mathematics2289

Social Sciences2140

Data Science, Analytics & Computer Technology2056

Physics1765

Computer Science1714

Humanities1556

Business & Management1480

Systems Engineering905

Literature865

Art, Design & Architecture814

Electrical Engineering810

Biology791

Chemistry700

Economics682

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Business & Management

1480

Systems Engineering905

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Art, Design & Architecture814

Electrical Engineering810

Biology791

Chemistry700

Economics682

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Music121

Linguistics108

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Sustainable Business26

Corporate Innovation19

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Environmental and Climate Justice1

MIT

Software Engineering Concepts

This is a reading and discussion subject on issues in the engineering of software systems and software development project design. It includes the present state of software engineering, what has been tried in the past, what worked, what did not, and why. Topics may differ in each offering, but will be chosen from: the software process and lifecycle; requirements and specifications; design principles; testing, formal analysis, and reviews; quality management and assessment; product and process metrics; COTS and reuse; evolution and maintenance; team organization and people management; and software engineering aspects of programming languages.

Gratis

MIT

Foundations of Computational and Systems Biology

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.

Gratis

MIT

Networks, Complexity and Its Applications

Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development.

Gratis

MIT

Essential Numerical Methods

This half-semester course introduces computational methods for solving physical problems, especially in nuclear applications. The course covers ordinary and partial differential equations for particle orbit, and fluid, field, and particle conservation problems; their representation and solution by finite difference numerical approximations; iterative matrix inversion methods; stability, convergence, accuracy and statistics; and particle representations of Boltzmann’s equation and methods of solution such as Monte-Carlo and particle-in-cell techniques.

Gratis

MIT

Systems Analysis of the Nuclear Fuel Cycle

This course provides an in-depth technical and policy analysis of various options for the nuclear fuel cycle. Topics include uranium supply, enrichment fuel fabrication, in-core physics and fuel management of uranium, thorium and other fuel types, reprocessing and waste disposal. Also covered are the principles of fuel cycle economics and the applied reactor physics of both contemporary and proposed thermal and fast reactors. Nonproliferation aspects, disposal of excess weapons plutonium, and transmutation of actinides and selected fission products in spent fuel are examined. Several state-of-the-art computer programs are provided for student use in problem sets and term papers.

Gratis

MIT

Engineering Design and Rapid Prototyping

This course provides students with an opportunity to conceive, design and implement a product, using rapid prototyping methods and computer-aid tools. The first of two phases challenges each student team to meet a set of design requirements and constraints for a structural component. A course of iteration, fabrication, and validation completes this manual design cycle. During the second phase, each team conducts design optimization using structural analysis software, with their phase one prototype as a baseline. Acknowledgements This course is made possible thanks to a grant by the alumni sponsored Teaching and Education Enhancement Program (Class of ‘51 Fund for Excellence in Education, Class of ‘55 Fund for Excellence in Teaching, Class of ‘72 Fund for Educational Innovation). The instructors gratefully acknowledge the financial support. The course was approved by the Undergraduate Committee of the MIT Department of Aeronautics and Astronautics in 2003. The instructors thank Prof. Manuel Martinez-Sanchez and the committee members for their support and suggestions.

Gratis

MIT

Topics in Phonology

This course introduces students to the theory and practice of modeling phonology, with an empirical focus on modeling the discovery of static phonotactics, the discovery of alternations, learning in the midst of variation and exceptions, and the discovery of gradient patterns. This course is also intended to provide hands-on experience with various aspects of using and developing models, including preparing training data, running simulations, and interpreting their results.

Gratis

MIT

Systems Optimization

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, integer, and network optimization, and heuristic methods); Provide tools for interpreting and analyzing model-based solutions (sensitivity and post-optimality analysis, bounding techniques); and Develop the skills required to identify the opportunity and manage the implementation of an optimization-based decision support tool.

Gratis

MIT

Atomistic Computer Modeling of Materials (SMA 5107)

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure approaches, molecular dynamics, and Monte Carlo. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5107 (Atomistic Computer Modeling of Materials). Acknowledgements Support for this course has come from the National Science Foundation’s Division of Materials Research (grant DMR-0304019) and from the Singapore-MIT Alliance.

Gratis

MIT

System Identification

This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.

Gratis

MIT

Engineering, Economics and Regulation of the Electric Power Sector

The course presents an in-depth interdisciplinary perspective of electric power systems, with regulation providing the link among the engineering, economic, legal and environmental viewpoints. Generation dispatch, demand response, optimal network flows, risk allocation, reliability of service, renewable energy sources, ancillary services, tariff design, distributed generation, rural electrification, environmental impacts and strategic sustainability issues will be among the topics addressed under both traditional and competitive regulatory frameworks.

Gratis

MIT

Lean/Six Sigma Processes

Students of this course will develop a broad understanding of Lean/Six Sigma principles and practices, build capability to implement Lean/Six Sigma initiatives in manufacturing operations, and learn to operate with awareness of Lean/Six Sigma at the enterprise level. All course materials are organized around a common “single-point lesson” (SPL) format, with some of the SPLs provided by the instructor and guests and with some developed and delivered by student teams.

Gratis

MIT

Digital Design Fabrication

This course will guide graduate students through the process of using rapid prototyping and CAD/CAM devices in a studio environment. The class has a theoretical focus on machine use within the process of design. Each student is expected to have completed one graduate level of design computing with a full understanding of solid modeling in CAD. Students are also expected to have completed at least one graduate design studio.

Gratis

MIT

Fundamentals of Advanced Energy Conversion

This course covers fundamentals of thermodynamics, chemistry, and transport applied to energy systems. Topics include analysis of energy conversion and storage in thermal, mechanical, chemical, and electrochemical processes in power and transportation systems, with emphasis on efficiency, performance, and environmental impact. Applications include fuel reforming and alternative fuels, hydrogen, fuel cells and batteries, combustion, catalysis, combined and hybrid power cycles using fossil, nuclear and renewable resources.

Gratis

MIT

Probabilistic Systems Analysis and Applied Probability

This course introduces students to the modeling, quantification, and analysis of uncertainty. The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management. Course Format This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include: Lecture Videos by MIT Professor John Tsitsiklis Lecture Slides and Readings Recitation Problems and Solutions Recitation Help Videos by MIT Teaching Assistants Tutorial Problems and Solutions Tutorial Help Videos by MIT Teaching Assistants Problem Sets with Solutions Exams with Solutions Related Resource A complementary resource, Introduction to Probability, is provided by the videos developed for an EdX version of 6.041. These videos cover more or less the same content, in somewhat different order, and in somewhat more detail than the videotaped live lectures.

Gratis

MIT

Classical Mechanics: A Computational Approach

We will study the fundamental principles of classical mechanics, with a modern emphasis on the qualitative structure of phase space. We will use computational ideas to formulate the principles of mechanics precisely. Expression in a computational framework encourages clear thinking and active exploration. We will consider the following topics: the Lagrangian formulation; action, variational principles, and equations of motion; Hamilton’s principle; conserved quantities; rigid bodies and tops; Hamiltonian formulation and canonical equations; surfaces of section; chaos; canonical transformations and generating functions; Liouville’s theorem and Poincaré integral invariants; Poincaré-Birkhoff and KAM theorems; invariant curves and cantori; nonlinear resonances; resonance overlap and transition to chaos; properties of chaotic motion. Ideas will be illustrated and supported with physical examples. We will make extensive use of computing to capture methods, for simulation, and for symbolic analysis.

Gratis

MIT

Experimental Projects I

The Experimental Project Lab in the Department of Aeronautics and Astronautics is a two-semester course sequence: 16.621 Experimental Projects I (this course) and 16.622 Experimental Projects II. This site offers material on 16.621. In the course, two-person teams initiate a project of their own conception and design in 16.621 and then complete it in 16.622. For many students, this is a first encounter with research standards and techniques. It is a complicated course that requires a lot of interaction and support and also access to facilities and materials, but it is rewarding for students to explore an hypothesis under the guidance of a faculty advisor. This OCW site presents the building block materials of the course, which can provide only a profile of the course because the most important learning elements are the interactions between student team, faculty, project advisor, and shop staff and also between student team members. However, this site offers some of the preparation and guidance materials for students embarking on an experimental project. To emphasize the focus on communication skills, a set of study materials and examples of student work are provided.

Gratis

MIT

Systems Perspectives on Industrial Ecology

This course examines quantitative techniques for life cycle analysis of the impacts of materials extraction, processing use, and recycling; and economic analysis of materials processing, products, and markets. Student teams undertake a major case study using the latest methods of analysis and computer-based models of materials process.

Gratis

MIT

Engineering Apollo: The Moon Project as a Complex System

This course is a detailed technical and historical exploration of the Apollo project to “fly humans to the moon and return them safely to earth” as an example of a complex engineering system. Emphasis is on how the systems worked, the technical and social processes that produced them, mission operations, and historical significance. Guest lectures are featured by MIT-affiliated engineers who contributed to and participated in the Apollo missions. Students work in teams on a final project analyzing an aspect of the historical project to articulate and synthesize ideas in engineering systems.

Gratis

MIT

Logistical and Transportation Planning Methods

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Gratis

MIT

Data, Models, and Decisions

This course is designed to introduce first-year Sloan MBA students to the fundamental techniques of using data. In particular, the course focuses on various ways of modeling, or thinking structurally about decision problems in order to make informed management decisions.

Gratis

MIT

Introduction to Network Models

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.

Gratis

MIT

Introduction to 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.

Gratis

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