Searching for visualization : 63 results found | RSS Feed for this search

1 2 3

4.110J Design Across Scales, Disciplines and Problem Contexts (MIT) 4.110J Design Across Scales, Disciplines and Problem Contexts (MIT)

Description

This course explores the reciprocal relationships among design, science, and technology by covering a wide range of topics including industrial design, architecture, visualization and perception, design computation, material ecology, and environmental design and sustainability. Students will examine how transformations in science and technology have influenced design thinking and vice versa, as well as develop methodologies for design research and collaborate on design solutions to interdisciplinary problems. This course explores the reciprocal relationships among design, science, and technology by covering a wide range of topics including industrial design, architecture, visualization and perception, design computation, material ecology, and environmental design and sustainability. Students will examine how transformations in science and technology have influenced design thinking and vice versa, as well as develop methodologies for design research and collaborate on design solutions to interdisciplinary problems.

Subjects

4.110 | 4.110 | MAS.330 | MAS.330 | design | design | media | media | animation | animation | image | image | data | data | visualization | visualization | representation | representation | database | database | Processing | Processing | fabrication | fabrication | technology | technology | systems | systems | model | model | AI | AI | intelligence | intelligence | programming | programming | optimization | optimization | machine | machine | play | play | game | game | utopia | utopia | future | future | dystopia | dystopia | science fiction | science fiction | environment | environment | growth | growth | organization | organization

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

3.016 Mathematics for Materials Scientists and Engineers (MIT) 3.016 Mathematics for Materials Scientists and Engineers (MIT)

Description

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 C 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 C

Subjects

energetics | energetics | visualization | visualization | graph | graph | plot | plot | chart | chart | materials science | materials science | DMSE | DMSE | structure | structure | symmetry | symmetry | mechanics | mechanics | physicss | physicss | solids and soft materials | solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalue | eigenvalue | eigenvector | eigenvector | quadratic form | quadratic form | tensor operation | tensor operation | symmetry operation | symmetry operation | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | ODE | ODE | solution | solution | vector | vector | matrix | matrix | determinant | determinant | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walk | random walk | Mathematica | Mathematica | simulation | simulation

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-3.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

20.309 Biological Engineering II: Instrumentation and Measurement (MIT) 20.309 Biological Engineering II: Instrumentation and Measurement (MIT)

Description

Includes audio/video content: AV special element video. This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data. Enrollment preference is given to juniors and seniors. Includes audio/video content: AV special element video. This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data. Enrollment preference is given to juniors and seniors.

Subjects

DNA analysis | DNA analysis | Fourier analysis | Fourier analysis | FFT | FFT | DNA melting | DNA melting | electronics | electronics | microscopy | microscopy | microscope | microscope | probes | probes | biology | biology | atomic force microscope | atomic force microscope | AFM | AFM | scanning probe microscope | scanning probe microscope | image processing | image processing | MATLAB | MATLAB | convolution | convolution | optoelectronics | optoelectronics | rheology | rheology | fluorescence | fluorescence | noise | noise | detector | detector | optics | optics | diffraction | diffraction | optical trap | optical trap | 3D | 3D | 3-D | 3-D | three-dimensional imaging | three-dimensional imaging | visualization | visualization

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allavcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

CMS.633 Digital Humanities (MIT) CMS.633 Digital Humanities (MIT)

Description

This course examines the theory and practice of using computational methods in the emerging field of digital humanities. It develops an understanding of key digital humanities concepts, such as data representation, digital archives, information visualization, and user interaction through the study of contemporary research, in conjunction with working on real-world projects for scholarly, educational, and public needs. Students create prototypes, write design papers, and conduct user studies. This course examines the theory and practice of using computational methods in the emerging field of digital humanities. It develops an understanding of key digital humanities concepts, such as data representation, digital archives, information visualization, and user interaction through the study of contemporary research, in conjunction with working on real-world projects for scholarly, educational, and public needs. Students create prototypes, write design papers, and conduct user studies.

Subjects

digital humanities | digital humanities | data visualization | data visualization | data representation | data representation | digital archives | digital archives | humanities | humanities | data mining | data mining | databases | databases | GIS | GIS | design | design | prototype | prototype | programming | programming

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

STS.067 Scientific Visualization across Disciplines: A Critical Introduction (MIT) STS.067 Scientific Visualization across Disciplines: A Critical Introduction (MIT)

Description

This subject exposes students to a variety of visualization techniques so that they learn to understand the work involved in producing them and to critically assess the power and limits of each. Students concentrate on areas where visualizations are crucial for meaning making and data production. Drawing on scholarship in science and technology studies on visualization, critical art theory, and core discussions in science and engineering, students work through a series of case studies in order to become better readers and producers of visualizations. This subject exposes students to a variety of visualization techniques so that they learn to understand the work involved in producing them and to critically assess the power and limits of each. Students concentrate on areas where visualizations are crucial for meaning making and data production. Drawing on scholarship in science and technology studies on visualization, critical art theory, and core discussions in science and engineering, students work through a series of case studies in order to become better readers and producers of visualizations.

Subjects

Visualizations | Visualizations | visualization techniques | visualization techniques | Scientific Visualization | Scientific Visualization | critical art theory | critical art theory | Social Interaction Interfaces | Social Interaction Interfaces | Diagrams and Logic | Diagrams and Logic | Molecular Modeling | Molecular Modeling

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-STS.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.204 Planning, Communications, and Digital Media (MIT) 11.204 Planning, Communications, and Digital Media (MIT)

Description

This course focuses on methods of digital visualization and communication and their application to planning issues. Lectures will introduce a variety of methods for describing or representing a place and its residents, for simulating changes, for presenting visions of the future, and for engaging multiple actors in the process of guiding action. Through a series of laboratory exercises, students will apply these methods in the construction of a web-based portfolio. The portfolio is not only the final project for the course, but will serve as a container for other course work throughout the MCP program.This course aims to introduce students to (1) such persistent and recurring themes as place, race, power and the environment that face planners, (2) the role of digital technologies in repres This course focuses on methods of digital visualization and communication and their application to planning issues. Lectures will introduce a variety of methods for describing or representing a place and its residents, for simulating changes, for presenting visions of the future, and for engaging multiple actors in the process of guiding action. Through a series of laboratory exercises, students will apply these methods in the construction of a web-based portfolio. The portfolio is not only the final project for the course, but will serve as a container for other course work throughout the MCP program.This course aims to introduce students to (1) such persistent and recurring themes as place, race, power and the environment that face planners, (2) the role of digital technologies in repres

Subjects

planning | planning | communication | communication | digital | digital | media | media | communications | communications | visualization | visualization | the role of digital technologies | the role of digital technologies | mobilizing communities | mobilizing communities | Athena | Athena | Element K | Element K | the ESRI virtual campus | the ESRI virtual campus | Computer Resources Laboratory (CRL) | Computer Resources Laboratory (CRL) | Campus Wide Information Systems Support (CWIS) | Campus Wide Information Systems Support (CWIS) | the GIS Laboratory | the GIS Laboratory | Rotch Library | Rotch Library | software tools | software tools | Adobe Photoshop | Adobe Photoshop | Illustrator | Illustrator | ESRI's ArcView | ESRI's ArcView | Microsoft's Access | Microsoft's Access | Macromedia's Dreamweaver | Macromedia's Dreamweaver

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

22.00J Introduction to Modeling and Simulation (MIT) 22.00J Introduction to Modeling and Simulation (MIT)

Description

This course focuses on the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. Techniques and software for statistical sampling, simulation, data analysis and visualization. Use of statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal-footing with theory and experiment. Term project allows development of individual interest. Student mentoring by a coordinated This course focuses on the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. Techniques and software for statistical sampling, simulation, data analysis and visualization. Use of statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal-footing with theory and experiment. Term project allows development of individual interest. Student mentoring by a coordinated

Subjects

Quantum | Quantum | Modeling | Modeling | visualization | visualization | data analysis | data analysis | simulation | simulation | statistical sampling | statistical sampling | 22.00 | 22.00 | 1.021 | 1.021 | 3.021 | 3.021 | 10.333 | 10.333 | 18.361 | 18.361 | 2.030 | 2.030

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.501 Introduction to Technology and Cities (MIT) 11.501 Introduction to Technology and Cities (MIT)

Description

This seminar is an introduction to the usage and impacts of information and communication technologies (ICTs) on urban planning, the urban environment and communities. Students will explore how social relationships, our sense of community, the urban infrastructure, and planning practice have been affected by technological change. Literature reviews, guest speakers, and web surfing will provide examples and issues that are debated in class and homework exercises. We will examine metropolitan information infrastructures, urban modeling and visualization, e-government, collaborative planning, and cyber communities. Students will attend a regular Tuesday seminar and occasional seminars of invited speakers during lunchtime on Fridays or Mondays. During the past two decades, ICTs have become so This seminar is an introduction to the usage and impacts of information and communication technologies (ICTs) on urban planning, the urban environment and communities. Students will explore how social relationships, our sense of community, the urban infrastructure, and planning practice have been affected by technological change. Literature reviews, guest speakers, and web surfing will provide examples and issues that are debated in class and homework exercises. We will examine metropolitan information infrastructures, urban modeling and visualization, e-government, collaborative planning, and cyber communities. Students will attend a regular Tuesday seminar and occasional seminars of invited speakers during lunchtime on Fridays or Mondays. During the past two decades, ICTs have become so

Subjects

GIS | GIS | E-Government | E-Government | information and communication technology | information and communication technology | metropolitan information infrastructures | metropolitan information infrastructures | urban modeling and visualization | urban modeling and visualization | e-government | e-government | collaborative planning | collaborative planning | and cyber communities | and cyber communities | ICT | ICT | neighborhood | neighborhood | community | community | urban planning | urban planning | IT | IT

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-11.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

9.93 Cognitive Neuroscience of Remembering: Creating and Controlling Memory (MIT) 9.93 Cognitive Neuroscience of Remembering: Creating and Controlling Memory (MIT)

Description

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 survey course is intended to review memory and its impact on our lives. Memories make us who we are, and make us what we are going to become. The loss of memory in amnesia can cause us to lose ourselves. Memory provides a bridge between past and present. Through memory, past sensations, feelings, and ideas that have dropped from conscious awareness can be subsequently recovered to guide current thought and action. In this manner, memory allows us to locate our car in the parking lot at the end of the day or guides us to avoid retelling the same joke to the same friend. This seminar will focus on how memories a 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 survey course is intended to review memory and its impact on our lives. Memories make us who we are, and make us what we are going to become. The loss of memory in amnesia can cause us to lose ourselves. Memory provides a bridge between past and present. Through memory, past sensations, feelings, and ideas that have dropped from conscious awareness can be subsequently recovered to guide current thought and action. In this manner, memory allows us to locate our car in the parking lot at the end of the day or guides us to avoid retelling the same joke to the same friend. This seminar will focus on how memories a

Subjects

human memory | human memory | neural memory | neural memory | cognitive control | cognitive control | recall | recall | retrieval | retrieval | learning | learning | perception | perception | priming | priming | forgetting | forgetting | frontal lobe | frontal lobe | MRI | MRI | brain imaging | brain imaging | amnesia | amnesia | Alzheimer's | Alzheimer's | dementia | dementia | aging | aging | short-term memory | short-term memory | long-term memory | long-term memory | memory loss | memory loss | eyewitness | eyewitness | false memory | false memory | visualization | visualization

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-9.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

11.204 Planning, Communications, and Digital Media (MIT) 11.204 Planning, Communications, and Digital Media (MIT)

Description

This course focuses on methods of digital visualization and communication and their application to planning issues. Lectures will introduce a variety of methods for describing or representing a place and its residents, for simulating changes, for presenting visions of the future, and for engaging multiple actors in the process of guiding action. Through a series of laboratory exercises, students will apply these methods in the construction of a web-based portfolio. The portfolio is not only the final project for the course, but will serve as a container for other course work throughout the MCP program. This course aims to introduce students to (1) such persistent and recurring themes as place, race, power and the environment that face planners, (2) the role of digital technologies in repre This course focuses on methods of digital visualization and communication and their application to planning issues. Lectures will introduce a variety of methods for describing or representing a place and its residents, for simulating changes, for presenting visions of the future, and for engaging multiple actors in the process of guiding action. Through a series of laboratory exercises, students will apply these methods in the construction of a web-based portfolio. The portfolio is not only the final project for the course, but will serve as a container for other course work throughout the MCP program. This course aims to introduce students to (1) such persistent and recurring themes as place, race, power and the environment that face planners, (2) the role of digital technologies in repre

Subjects

planning | planning | communication | communication | digital | digital | media | media | communications | communications | visualization | visualization | the role of digital technologies | the role of digital technologies | mobilizing communities | mobilizing communities | Athena | Athena | Element K | Element K | the ESRI virtual campus | the ESRI virtual campus | Computer Resources Laboratory (CRL) | Computer Resources Laboratory (CRL) | Campus Wide Information Systems Support (CWIS) | Campus Wide Information Systems Support (CWIS) | the GIS Laboratory | the GIS Laboratory | Rotch Library | Rotch Library | software tools | software tools | Adobe Photoshop | Adobe Photoshop | Illustrator | Illustrator | ESRI's ArcView | ESRI's ArcView | Microsoft's Access | Microsoft's Access | Macromedia's Dreamweaver | Macromedia's Dreamweaver

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-11.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

22.00J Introduction to Modeling and Simulation (MIT) 22.00J Introduction to Modeling and Simulation (MIT)

Description

This course surveys the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. It covers techniques and software for statistical sampling, simulation, data analysis and visualization, and uses statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications are drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal footing with theory and experiment. A term project allows development of individual interests. Students are mentor This course surveys the basic concepts of computer modeling in science and engineering using discrete particle systems and continuum fields. It covers techniques and software for statistical sampling, simulation, data analysis and visualization, and uses statistical, quantum chemical, molecular dynamics, Monte Carlo, mesoscale and continuum methods to study fundamental physical phenomena encountered in the fields of computational physics, chemistry, mechanics, materials science, biology, and applied mathematics. Applications are drawn from a range of disciplines to build a broad-based understanding of complex structures and interactions in problems where simulation is on equal footing with theory and experiment. A term project allows development of individual interests. Students are mentor

Subjects

computer modeling | computer modeling | discrete particle system | discrete particle system | continuum | continuum | continuum field | continuum field | statistical sampling | statistical sampling | data analysis | data analysis | visualization | visualization | quantum | quantum | quantum method | quantum method | chemical | chemical | molecular dynamics | molecular dynamics | Monte Carlo | Monte Carlo | mesoscale | mesoscale | continuum method | continuum method | computational physics | computational physics | chemistry | chemistry | mechanics | mechanics | materials science | materials science | biology; applied mathematics | biology; applied mathematics | fluid dynamics | fluid dynamics | heat | heat | fractal | fractal | evolution | evolution | melting | melting | gas | gas | structural mechanics | structural mechanics | FEM | FEM | finite element | finite element | biology | biology | applied mathematics | applied mathematics | 1.021 | 1.021 | 2.030 | 2.030 | 3.021 | 3.021 | 10.333 | 10.333 | 18.361 | 18.361 | HST.588 | HST.588 | 22.00 | 22.00

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to

Subjects

programming languages | techniques used by physical scientists | programming languages | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification | algorithms | algorithms | formula | formula | formulae | formulae | computer programs | computer programs | graphics | graphics | computing languages | computing languages | structure | structure | documentation | documentation | program interface | program interface | syntax | syntax | advanced modeling | advanced modeling | simulation systems | simulation systems

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

6.883 Program Analysis (MIT) 6.883 Program Analysis (MIT)

Description

6.883 is a graduate seminar that investigates a variety of program analysis techniques that address software engineering tasks. Static analysis topics include abstract interpretation (dataflow), type systems, model checking, decision procedures (SAT, BDDs), theorem-proving. Dynamic analysis topics include testing, fault isolation (debugging), model inference, and visualization. While the course focuses on the design and implementation of programming tools, the material will be useful to anyone who wishes to improve his or her programming or understand the state of the art. Students are expected to read classic and current technical papers, actively participate in class discussion, perform small exercises that provide experience with a variety of tools, and complete a team research project. 6.883 is a graduate seminar that investigates a variety of program analysis techniques that address software engineering tasks. Static analysis topics include abstract interpretation (dataflow), type systems, model checking, decision procedures (SAT, BDDs), theorem-proving. Dynamic analysis topics include testing, fault isolation (debugging), model inference, and visualization. While the course focuses on the design and implementation of programming tools, the material will be useful to anyone who wishes to improve his or her programming or understand the state of the art. Students are expected to read classic and current technical papers, actively participate in class discussion, perform small exercises that provide experience with a variety of tools, and complete a team research project.

Subjects

program analysis | program analysis | static analysis | static analysis | abstract interpretation (dataflow) | abstract interpretation (dataflow) | type systems | type systems | model checking | model checking | decision procedures (SAT | decision procedures (SAT | BDDs) | BDDs) | theorem-proving | theorem-proving | dynamic analysis | dynamic analysis | testing | testing | fault isolation (debugging) | fault isolation (debugging) | model inference | and visualization | model inference | and visualization | decision procedures (SAT | BDDs) | decision procedures (SAT | BDDs)

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-6.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

15.874 System Dynamics for Business Policy (MIT) 15.874 System Dynamics for Business Policy (MIT)

Description

15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using system dynamics. 15.874 is a full semester course and 15.871 is a half semester course. The two classes meet together and cover the same material for the first half of the term. In the second half of the semester, only 15.874 continues. 15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using system dynamics. 15.874 is a full semester course and 15.871 is a half semester course. The two classes meet together and cover the same material for the first half of the term. In the second half of the semester, only 15.874 continues.

Subjects

system dynamics modeling applied to corporate strategy | system dynamics modeling applied to corporate strategy | simulation models | simulation models | quot; | quot; | management "flight simulators" | management "flight simulators" | high-performance organizations | high-performance organizations | growth strategy | growth strategy | management of technology | management of technology | operations | operations | project management | project management | effective use of modeling in the real world | effective use of modeling in the real world | business strategy | business strategy | system dynamics modeling | system dynamics modeling | corporate strategy | corporate strategy | case studies | case studies | business policies | business policies | visualizations | visualizations | business structures | business structures | microworlds | microworlds | role playing games | role playing games | policy design | policy design

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

3.021J Introduction to Modeling and Simulation (MIT) 3.021J Introduction to Modeling and Simulation (MIT)

Description

This course explores the basic concepts of computer modeling and simulation in science and engineering. We'll use techniques and software for simulation, data analysis and visualization. Continuum, mesoscale, atomistic and quantum methods are used to study fundamental and applied problems in physics, chemistry, materials science, mechanics, engineering, and biology. Examples drawn from the disciplines above are used to understand or characterize complex structures and materials, and complement experimental observations. This course explores the basic concepts of computer modeling and simulation in science and engineering. We'll use techniques and software for simulation, data analysis and visualization. Continuum, mesoscale, atomistic and quantum methods are used to study fundamental and applied problems in physics, chemistry, materials science, mechanics, engineering, and biology. Examples drawn from the disciplines above are used to understand or characterize complex structures and materials, and complement experimental observations.

Subjects

computer modeling | computer modeling | discrete particle system | discrete particle system | continuum | continuum | continuum field | continuum field | statistical sampling | statistical sampling | data analysis | data analysis | visualization | visualization | quantum | quantum | quantum method | quantum method | chemical | chemical | molecular dynamics | molecular dynamics | Monte Carlo | Monte Carlo | mesoscale | mesoscale | continuum method | continuum method | computational physics | computational physics | chemistry | chemistry | mechanics | mechanics | materials science | materials science | biology | biology | applied mathematics | applied mathematics | fluid dynamics | fluid dynamics | heat | heat | fractal | fractal | evolution | evolution | melting | melting | gas | gas | structural mechanics | structural mechanics | FEM | FEM | finite element | finite element

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | visualization techniques | visualization techniques | numerical analysis | numerical analysis | dissemination | dissemination

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-12.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

1.124J Foundations of Software Engineering (MIT) 1.124J Foundations of Software Engineering (MIT)

Description

This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J. This is a foundation subject in modern software development techniques for engineering and information technology. The design and development of component-based software (using C# and .NET) is covered; data structures and algorithms for modeling, analysis, and visualization; basic problem-solving techniques; web services; and the management and maintenance of software. Includes a treatment of topics such as sorting and searching algorithms; and numerical simulation techniques. Foundation for in-depth exploration of image processing, computational geometry, finite element methods, network methods and e-business applications. This course is a core requirement for the Information Technology M. Eng. program. This class was also offered in Course 13 (Department of Ocean Engineering) as 13.470J.

Subjects

modern software development | modern software development | engineering and information technology | engineering and information technology | component-based software | component-based software | C# | C# | .NET | .NET | data structures | data structures | algorithms for modeling | algorithms for modeling | analysis | analysis | visualization | visualization | basic problem-solving techniques | basic problem-solving techniques | web services | web services | management and maintenance of software | management and maintenance of software | sorting | sorting | searching | searching | algorithms | algorithms | numerical simulation techniques | numerical simulation techniques | image processing | image processing | computational geometry | computational geometry | finite element methods | finite element methods | network methods | network methods | e-business applications | e-business applications | classes | classes | objects | objects | inheritance | inheritance | virtual functions | virtual functions | abstract classes | abstract classes | polymorphism | polymorphism | Java applications | Java applications | applets | applets | Abstract Windowing Toolkit | Abstract Windowing Toolkit | Graphics | Graphics | Threads | Threads | Java | Java | C++ | C++ | information technology | information technology | engineering | engineering | modeling algorithms | modeling algorithms | basic problem-solving | basic problem-solving | software management | software management | software maintenance | software maintenance | searching algorithms | searching algorithms | numerical simulation | numerical simulation | object oriented programming | object oriented programming | 13.470J | 13.470J | 1.124 | 1.124 | 2.159 | 2.159 | 13.470 | 13.470

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

4.206 Introduction to Design Computing (MIT) 4.206 Introduction to Design Computing (MIT)

Description

This course will introduce students to architectural design and computation through the use of computer modeling, rendering and digital fabrication. The course focuses on teaching architectural design with CAD drawing, modeling, rendering and rapid prototyping. Students will be required to build computer models that will lead to a full package of architectural explorations within a computational environment. Each semester will explore a particular historical period in architecture and the work of a selected architect. This course will introduce students to architectural design and computation through the use of computer modeling, rendering and digital fabrication. The course focuses on teaching architectural design with CAD drawing, modeling, rendering and rapid prototyping. Students will be required to build computer models that will lead to a full package of architectural explorations within a computational environment. Each semester will explore a particular historical period in architecture and the work of a selected architect.

Subjects

architectural design and computation | architectural design and computation | computer modeling | computer modeling | rendering | rendering | digital fabrication | digital fabrication | exploration of space | exploration of space | place making | place making | computer rendering | computer rendering | design construction | design construction | CAD CAM fabrication | CAD CAM fabrication | computer models | computer models | computer aided drawings | computer aided drawings | rapid prototyped models | rapid prototyped models | architecture | architecture | design | design | computation | computation | representational mediums | representational mediums | architectural design | architectural design | complex phenomena | complex phenomena | constructs | constructs | information visualization | information visualization | programming | programming | computer graphics | computer graphics | data respresentation | data respresentation

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

MAS.965 Social Visualization (MIT) MAS.965 Social Visualization (MIT)

Description

Millions of people are on-line today and the number is rapidly growing - yet this virtual crowd is often invisible. In this course we will examine ways of visualizing people, their activities and their interactions. Students will study the cognitive and cultural basis for social visualization through readings drawn from sociology, psychology and interface design and they will explore new ways of depicting virtual crowds and mapping electronic spaces through a series of design exercises. Millions of people are on-line today and the number is rapidly growing - yet this virtual crowd is often invisible. In this course we will examine ways of visualizing people, their activities and their interactions. Students will study the cognitive and cultural basis for social visualization through readings drawn from sociology, psychology and interface design and they will explore new ways of depicting virtual crowds and mapping electronic spaces through a series of design exercises.

Subjects

social visualization | social visualization | internet | internet | chat | chat | mediation | mediation | faces | faces | emotion | emotion | emoticons | emoticons | cognition | cognition | recognition | recognition | personality | personality | perception | perception | depiction | depiction | virtual presence | virtual presence | conversation | conversation | rhythym | rhythym | psychology | psychology | representation | representation | design | design | privacy | privacy

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-MAS.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

17.914 International Politics in the New Century - via Simulation, Interactive Gaming, and 'Edutainment' (MIT) 17.914 International Politics in the New Century - via Simulation, Interactive Gaming, and 'Edutainment' (MIT)

Description

This workshop is designed to introduce students to different perspectives on politics and the state of the world through new visualization techniques and approaches to interactive political gaming (and selective 'edutainment'). Specifically, we shall explore applications of interactive tools (such as video and web-based games, blogs or simulations) to examine critical challenges in international politics of the 21C century focusing specifically on general insights and specific understandings generated by operational uses of core concepts in political science. This workshop is designed to introduce students to different perspectives on politics and the state of the world through new visualization techniques and approaches to interactive political gaming (and selective 'edutainment'). Specifically, we shall explore applications of interactive tools (such as video and web-based games, blogs or simulations) to examine critical challenges in international politics of the 21C century focusing specifically on general insights and specific understandings generated by operational uses of core concepts in political science.

Subjects

Workshop | Workshop | political science | political science | politics | politics | world | world | visualization | visualization | techniques | techniques | interactive | interactive | gaming | gaming | edutainment | edutainment | interactive tools | interactive tools | video | video | web-based games | web-based games | blogs | blogs | simulations | simulations | international | international | twenty-first century | twenty-first century

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-17.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++; Matlab | C++; Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification. | methods of dissemination and verification. | C++ | C++ | Matlab | Matlab | programming languages | techniques used by physical scientists | programming languages | techniques used by physical scientists

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

RES.6-009 How to Process, Analyze and Visualize Data (MIT) RES.6-009 How to Process, Analyze and Visualize Data (MIT)

Description

This course is an introduction to data cleaning, analysis and visualization. We will teach the basics of data analysis through concrete examples. You will learn how to take raw data, extract meaningful information, use statistical tools, and make visualizations. This was offered as a non-credit course 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 is an introduction to data cleaning, analysis and visualization. We will teach the basics of data analysis through concrete examples. You will learn how to take raw data, extract meaningful information, use statistical tools, and make visualizations. This was offered as a non-credit course 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.

Subjects

data analysis | data analysis | data cleaning | data cleaning | visualization | visualization | statistics | statistics | hypothesis testing | hypothesis testing | regression | regression | text processing | text processing | large datasets | large datasets | Hadoop | Hadoop | MapReduce | MapReduce

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-RES.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata

7.345 Vascular Development in Life, Disease and Cancer Medicine (MIT) 7.345 Vascular Development in Life, Disease and Cancer Medicine (MIT)

Description

The growth of blood vessels, a process known as angiogenesis, is one of the earliest events in mammalian development and is regulated by a sensitive interplay of growth factors and other molecules. In this course, we will discuss the key molecular regulators of blood vessel development as well as the techniques and experimental systems that have been utilized by vascular biologists. We will also examine the success of several anti-angiogenic treatments that have been approved by the Food and Drug Administration (FDA), that inhibit the pro-angiogenic vascular endothelial growth factor, VEGF, and that are now being used to treat age-related macular degeneration. Finally, we will explore how during the course of cancer progression, establishment of a blood supply into a tumor can lead to the The growth of blood vessels, a process known as angiogenesis, is one of the earliest events in mammalian development and is regulated by a sensitive interplay of growth factors and other molecules. In this course, we will discuss the key molecular regulators of blood vessel development as well as the techniques and experimental systems that have been utilized by vascular biologists. We will also examine the success of several anti-angiogenic treatments that have been approved by the Food and Drug Administration (FDA), that inhibit the pro-angiogenic vascular endothelial growth factor, VEGF, and that are now being used to treat age-related macular degeneration. Finally, we will explore how during the course of cancer progression, establishment of a blood supply into a tumor can lead to the

Subjects

angiogenesis | angiogenesis | growth factors | growth factors | VEGF | VEGF | microscopic visualization | microscopic visualization | intravital imaging | intravital imaging | anti-angiogenic treatments | anti-angiogenic treatments | macular degeneration | macular degeneration | cancer progression | cancer progression | tumor blood vessels | tumor blood vessels

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses-7.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

All metadata

See all metadata