This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).

This class covers basic concepts of nuclear physics with emphasis on nuclear structure and interactions of radiation with matter. Topics include elementary quantum theory; nuclear forces; shell structure of the nucleus; alpha, beta and gamma radioactive decays; interactions of nuclear radiations (charged particles, gammas, and neutrons) with matter; nuclear reactions; fission and fusion.

This course entitled “Introduction to Assitive Technology Typesand Categories" was prepared and designed by Mada Center, Qatar. It is part of the program : "Introduction to ICT Accessibility and Inclusive Design".

Bioengineering at MIT is represented by the diverse curricula offered by most Departments in the School of Engineering. This course samples the wide variety of bioengineering options for students who plan to major in one of the undergraduate Engineering degree programs. The beginning lectures describe the science basis for bioengineering with particular emphasis on molecular cell biology and systems biology. Bioengineering faculty will then describe the bioengineering options in a particular engineering course as well as the type of research conducted by faculty in the department.

This class is a project-based introduction to the engineering of synthetic biological systems. Throughout the term, students develop projects that are responsive to real-world problems of their choosing, and whose solutions depend on biological technologies. Lectures, discussions, and studio exercises will introduce (1) components and control of prokaryotic and eukaryotic behavior, (2) DNA synthesis, standards, and abstraction in biological engineering, and (3) issues of human practice, including biological safety; security; ownership, sharing, and innovation; and ethics. Enrollment preference is given to freshmen.
This subject was originally developed and first taught in Spring 2008 by Drew Endy and Natalie Kuldell. Many of Drew's materials are used in this Spring 2009 version, and are included with his permission.
This OCW Web site is based on the OpenWetWare class Wiki, found at OpenWetWare: 20.020 (S09)

The discipline of Biosystems Engineering emerged in the 1990s from the traditional strongholds of agricultural engineering and food engineering. Biosystems engineering integrates engineering science and design with applied biological, environmental, and agricultural sciences. Introduction to Biosystems Engineering is targeted at 1st and 2nd year university-level students with an interest in biosystems engineering but who are not yet familiar with the breadth and depth of the subject. It is designed as a coherent educational resource, also available for download as individual digital chapters. The book can be used as a localized, customizable text for introductory courses in Biosystems Engineering globally. It is written as a series of stand-alone chapters organized under six major topics: Food and Bioprocessing; Environment; Buildings and Infrastructure; Information and Communications Technology and Data; Machinery Systems; and Energy. Each chapter is organized around stated learning outcomes and describes key concepts, applications of the concepts, and worked examples.

The course aims at providing a fundamental understanding of the physics related to buildings and to propose an overview of the various issues that have to be adequately combined to offer the occupants a physical, functional and psychological well-being. Students will be guided through the different components, constraints and systems of a work of architecture. These will be examined both independently and in the manner in which they interact and affect one another.

This is a fast-paced introductory course to the C++ programming language. It is intended for those with little programming background, though prior programming experience will make it easier, and those with previous experience will still learn C++-specific constructs and concepts.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Ever hang your head in shame after your Python program wasn't as fast as your friend's C program? Ever wish you could use objects without having to use Java? Join us for this fun introduction to C and C++! We will take you through a tour that will start with writing simple C programs, go deep into the caves of C memory manipulation, resurface with an introduction to using C++ classes, dive deeper into advanced C++ class use and the C++ Standard Template Libraries. We'll wrap up by teaching you some tricks of the trade that you may need for tech interviews.
We see this as a "C/C++ empowerment" course: we want you to come away understanding

why you would want to use C over another language (control over memory, probably for performance reasons),
why you would want to use C++ rather than C (objects), and
how to be useful in C and C++.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

This course provides a fast-paced introduction to the C and C++ programming languages. You will learn the required background knowledge, including memory management, pointers, preprocessor macros, object-oriented programming, and how to find bugs when you inevitably use any of those incorrectly. There will be daily assignments and a small-scale individual project.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

1.012 introduces students to the theory, tools, and techniques of engineering design and creative problem-solving, as well as design issues and practices in civil engineering. The course includes several design cases, with an emphasis on built facilities (e.g., buildings, bridges and roads). Project design explicitly concerns technical approaches as well as consideration of the existing built environment, natural environment, economic and social factors, and expected life span. A large design case is introduced, which is used in the subsequent specialty area design subjects (1.031, 1.041, 1.051) and the capstone design subject (1.013).

In this sophomore design course, you will be challenged with three design tasks: a first concerning water resources/treatment, a second concerning structural design, and a third focusing on the conceptual (re)design of a large system, Boston's Back Bay. The first two tasks require the design, fabrication and testing of hardware. Several laboratory experiments will be carried out and lectures will be presented to introduce students to the conceptual and experimental basis for design in both domains.
This course was based in large part on the Fall 2005 offering of 1.101, developed by Prof. Harold Hemond.

In this sophomore design course, you will be challenged with three design tasks: a first concerning water resources/treatment, a second concerning structural design, and a third focusing on the conceptual (re)design of a large system, Boston’s Back Bay. The first two tasks require the design, fabrication and testing of hardware. Several laboratory experiments will be carried out and lectures will be presented to introduce students to the conceptual and experimental basis for design in both domains. This course was based in large part on the Fall 2005 offering of 1.101, developed by Prof. Harold Hemond.

This sophomore-level course is a project-oriented introduction to the principles and practice of engineering design. Design projects and exercises are chosen that relate to the built and natural environments. Emphasis is placed on achieving function and sustainability through choice of materials and processes, compatibility with natural cycles, and the use of active or adaptive systems. The course also encourages development of hands-on skills, teamwork, and communication; exercises and projects engage students in the building, implementation, and testing of their designs.

This course examines signals, systems and inference as unifying themes in communication, control and signal processing. Topics include input-output and state-space models of linear systems driven by deterministic and random signals; time- and transform-domain representations in discrete and continuous time; group delay; state feedback and observers; probabilistic models; stochastic processes, correlation functions, power spectra, spectral factorization; least-mean square error estimation; Wiener filtering; hypothesis testing; detection; matched filters.

This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.
Visit the Seung Lab Web site.

This is an introductory course on computational thinking. We use the Julia programming language to approach real-world problems in varied areas, applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole. Topics include image analysis, particle dynamics and ray tracing, epidemic propagation, and climate modeling.

This class uses revolutionary programmable interactivity to combine material from three fields -- Computer Science + Mathematics + Applications -- creating an engaging, efficient learning solution to prepare students to be sophisticated and intuitive thinkers, programmers, and solution providers for the modern interconnected online world.
Upon completion, students are well trained to be scientific “trilinguals,” seeing and experimenting with mathematics interactively as math is meant to be seen, and ready to participate and contribute to open source development of large projects and ecosystems.

6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.

This half-semester course introduces computational thinking through applications of data science, artificial intelligence, and mathematical models using the Julia programming language. This Spring 2020 version is a fast-tracked curriculum adaptation to focus on applications to COVID-19 responses.
See the MIT News article Computational Thinking Class Enables Students to Engage in Covid-19 Response