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6.837 Computer Graphics (MIT) 6.837 Computer Graphics (MIT)

Description

6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points. 6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.

Subjects

data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures | data structures | algorithms | algorithms | presenting data visually | presenting data visually | programming | programming | computer graphics | computer graphics | computer graphics applications | computer graphics applications | ray tracing | ray tracing | ray casting | ray casting | transformation | transformation | hierarchy | hierarchy | illumination | illumination | shading | shading | acceleration structures | acceleration structures | animation | animation | image-based rendering | image-based rendering | curves | curves | surfaces | surfaces | key frames | key frames | perspective | perspective | rasterization | rasterization | clipping | clipping | visibility | visibility | rendering | rendering | radiosity | radiosity | colors | colors | altialiasing | altialiasing | texture mapping | texture mapping | procedural textures | procedural textures | shadows | shadows | graphics hardware | graphics hardware

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

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Readme file for Introduction to OO Programming in Java

Description

This readme file contains details of links to all the Introduction to OO Programming in Java module's material held on Jorum and information about the module as well.

Subjects

ukoer | programming task guide | programming lecture | programming reading material | software design reading material | classes guide | libraries lecture | classes reading material | classes visual aid | software objects guide | graphics reading material | attributes reading material | attributes visual guide | naming conventions reading material | code reading material | java keywords reading material | variables visual guide | arithmetic reading material | java assignment | making decisions task guide | making decisions lecture | making decisions reading material | boolean expressions visual guide | repetition reading material | while loops visual guide | methods reading material | methods practical | access modifiers reading material | objects reading material | classes assignment | classes practical | child classes task guide | inheritance task guide | extending classes lecture | inheritance reading material | inheritance visual guide | inheritance practical | graphics task guide | awt reading material | graphics visual aid | awt class library reading material | event-driven programming reading material | scrollbars reading material | reflective practice visual guide | mobile phone task guide | mobile phone lecture | fixed repitition reading material | fixed repitition visual guide | mobile phone library reading material | mobile phone reading material | arrays task guide | arrays lecture | arrays reading material | arrays visual guide | creating software objects reading material | software objects visual guide | java practical | generic array list task guide | overriding methods reading material | menu and switch task guide | multi-way decisions reading material | multi-way decisions visual guide | searching task guide | searching lecture | searching reading material | software quality task guide | software quality lecture | software quality reading material | programming assignment | applet reading material | classes visual guide | object-oriented programming | object-oriented | programming | java | problem solving | java program | software design | programming languages | computers | class task guide | class reading material | class assignment | class practical | java classes | variables | attributes | arithmetic | java class | classes and arithmetic | classes | class | decisions | boolean expression | boolean expressions | repetition | methods | aggregate classes | access modifier | access modifiers | child classes | inheritance | child class | graphics | awt class library | fixed repetition | for loop | for loops | array | arrays | iteration | software object | definite iteration | generic lists | generic array list | cast | casting | overriding method | overriding methods | generic list | menu-driven program | menu-driven programs | multi-way decisions | menu and switch | search | searching | software quality | testing | software quality and testing | assessment | computers task guide | programming languages task guide | software design task guide | java program task guide | problem-solving task guide | problem solving task guide | object-oriented programming task guide | java task guide | object-oriented task guide | object oriented task guide | computers lecture | programming languages lecture | software design lecture | java program lecture | problem solving lecture | object-oriented programming lecture | java lecture | object oriented programming lecture | object-oriented lecture | computers reading material | programming languages reading material | java program reading material | problem solving reading material | object-oriented programming reading material | java reading material | object-oriented reading material | object oriented reading material | java classes task guide | variables task guide | attributes task guide | arithmetic task guide | java class task guide | classes and arithmetic task guide | classes task guide | java classes lecture | variables lecture | attributes lecture | arithmetic lecture | java class lecture | classes and arithmetic lecture | classes lecture | class lecture | java classes reading material | variables reading material | java class reading material | classes and arithmetic reading material | java classes visual aid | variables visual aid | attributes visual aid | arithmetic visual aid | java class visual aid | classes and arithmetic visual aid | class visual aid | java visual aid | object-oriented programming visual aid | programming visual aid | object-oriented visual aid | decisions task guide | boolean expression task guide | boolean expressions task guide | repetition task guide | methods task guide | decisions lecture | boolean expression lecture | boolean expressions lecture | repetition lecture | methods lecture | decisions reading material | boolean expression reading material | boolean expressions reading material | decisions visual aid | boolean expression visual aid | boolean expressions visual aid | repetition visual aid | methods visual aid | decisions practical | boolean expression practical | boolean expressions practical | repetition practical | programming practical | object oriented programming practical | object-oriented programming practical | object-oriented practical | object oriented practical | aggregate classes task guide | access modifier task guide | access modifiers task guide | aggregate classes lecture | access modifier lecture | access modifiers lecture | aggregate classes reading material | access modifier reading material | aggregate classes assignment | java classes assignment | access modifier assignment | access modifiers assignment | object oriented programming assignment | object-oriented programming assignment | object-oriented assignment | object oriented assignment | child class task guide | child classes lecture | inheritance lecture | child class lecture | child classes reading material | child class reading material | child classes visual aid | inheritance visual aid | child class visual aid | awt class library task guide | graphics lecture | awt class library lecture | awt class library visual aid | graphics assignment | awt class library assignment | fixed repetition task guide | fixed repetition lecture | fixed repetition visual aid | fixed repetition reading material | for loop task guide | for loops task guide | array task guide | iteration task guide | software object task guide | definite iteration task guide | for loop lecture | for loops lecture | array lecture | iteration lecture | software object lecture | definite iteration lecture | for loop reading material | for loops reading material | array reading material | iteration reading material | software object reading material | definite iteration reading material | for loop visual aid | for loops visual aid | array visual aid | arrays visual aid | iteration visual aid | software object visual aid | definite iteration visual aid | generic lists task guide | cast task guide | casting task guide | overriding method task guide | overriding methods task guide | generic list task guide | generic lists lecture | generic array list lecture | cast lecture | casting lecture | overriding method lecture | overriding methods lecture | generic list lecture | generic lists reading material | generic array list reading material | cast reading material | casting reading material | overriding method reading material | generic list reading material | menu-driven program task guide | menu-driven programs task guide | multi-way decisions task guide | menu-driven program lecture | menu-driven programs lecture | multi-way decisions lecture | menu and switch lecture | menu-driven program reading material | menu-driven programs reading material | menu and switch reading material | menu-driven program visual aid | menu-driven programs visual aid | multi-way decisions visual aid | menu and switch visual aid | search task guide | search lecture | search reading material | testing task guide | software quality and testing task guide | testing lecture | software quality and testing lecture | testing reading material | software quality and testing reading material | assessment reading material | assessment assignment | fixed repetition practical | jcreator guide | g622 | oo | oop | oo programming | awt | oo programming task guide | oop task guide | oo task guide | g622 task guide | oo programming lecture | oop lecture | oo lecture | g622 lecture | oo programming reading material | oop reading material | oo reading material | g622 reading material | g622 visual aid | oop visual aid | oo visual aid | oo programming visual aid | g622 practical | oo practical | oo programming practical | oop practical | g622 assignment | oo assignment | oop assignment | oo programming assignment | awt task guide | awt lecture | awt visual aid | awt assignment | Computer science | I100

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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6.837 Computer Graphics (MIT)

Description

6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.

Subjects

data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures | algorithms | presenting data visually | programming | computer graphics | computer graphics applications | ray tracing | ray casting | transformation | hierarchy | illumination | shading | acceleration structures | animation | image-based rendering | curves | surfaces | key frames | perspective | rasterization | clipping | visibility | rendering | radiosity | colors | altialiasing | texture mapping | procedural textures | shadows | graphics hardware

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

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6.837 Computer Graphics (MIT)

Description

6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.

Subjects

data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures | algorithms | presenting data visually | programming | computer graphics | computer graphics applications | ray tracing | ray casting | transformation | hierarchy | illumination | shading | acceleration structures | animation | image-based rendering | curves | surfaces | key frames | perspective | rasterization | clipping | visibility | rendering | radiosity | colors | altialiasing | texture mapping | procedural textures | shadows | graphics hardware

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

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6.837 Computer Graphics (MIT)

Description

6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.

Subjects

data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures | algorithms | presenting data visually | programming | computer graphics | computer graphics applications | ray tracing | ray casting | transformation | hierarchy | illumination | shading | acceleration structures | animation | image-based rendering | curves | surfaces | key frames | perspective | rasterization | clipping | visibility | rendering | radiosity | colors | altialiasing | texture mapping | procedural textures | shadows | graphics hardware

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

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6.837 Computer Graphics (MIT)

Description

6.837 offers an introduction to computer graphics hardware, algorithms, and software. Topics include: line generators, affine transformations, line and polygon clipping, splines, interactive techniques, perspective projection, solid modeling, hidden surface algorithms, lighting models, shading, and animation. Substantial programming experience is required. This course is worth 6 Engineering Design Points.

Subjects

data structures; algorithms; presenting data visually; programming; computer graphics; computer graphics applications; ray tracing; ray casting; transformation; hierarchy | data structures | algorithms | presenting data visually | programming | computer graphics | computer graphics applications | ray tracing | ray casting | transformation | hierarchy | illumination | shading | acceleration structures | animation | image-based rendering | curves | surfaces | key frames | perspective | rasterization | clipping | visibility | rendering | radiosity | colors | altialiasing | texture mapping | procedural textures | shadows | graphics hardware

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 https://ocw.mit.edu/terms/index.htm

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6.189 A Gentle Introduction to Programming Using Python (MIT) 6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

This 6-unit P/D/F course will provide a gentle introduction to programming using Python for highly motivated students with little or no prior experience in programming computers over the first two weeks of IAP. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. Lectures will be interactive, featuring in-class exercises with lots of support from the course staff. This class is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs This 6-unit P/D/F course will provide a gentle introduction to programming using Python for highly motivated students with little or no prior experience in programming computers over the first two weeks of IAP. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. Lectures will be interactive, featuring in-class exercises with lots of support from the course staff. This class is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs

Subjects

python | python | programming | programming | introduction to programming | introduction to programming | programming for beginners | programming for beginners | variables | variables | operators | operators | control flow | control flow | functions | functions | strings | strings | lists | lists | environment diagrams | environment diagrams | list comprehensions | list comprehensions | hangman | hangman | dictionaries | dictionaries | graphics | graphics | python graphics | python graphics | objects | objects | oop | oop | inheritance | inheritance | tetris | tetris | tetris game | tetris game

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

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14.462 Advanced Macroeconomics II (MIT) 14.462 Advanced Macroeconomics II (MIT)

Description

14.462 is the second semester of the second-year Ph.D. macroeconomics sequence. The course is intended to introduce the students, not only to particular areas of current research, but also to some very useful analytical tools. It covers a selection of topics that varies from year to year. Recent topics include: Growth and Fluctuations Heterogeneity and Incomplete Markets Optimal Fiscal Policy Time Inconsistency Reputation Coordination Games and Macroeconomic Complementarities Information 14.462 is the second semester of the second-year Ph.D. macroeconomics sequence. The course is intended to introduce the students, not only to particular areas of current research, but also to some very useful analytical tools. It covers a selection of topics that varies from year to year. Recent topics include: Growth and Fluctuations Heterogeneity and Incomplete Markets Optimal Fiscal Policy Time Inconsistency Reputation Coordination Games and Macroeconomic Complementarities Information

Subjects

macroeconomics research; analytical tools; analysis; endogenous growth; coordintation; incomplete markets; technolgy; distribution; employment; intellectual property rights; bounded rationality; demographics; complementarities; amplification; recursive equilibria; uncertainty; morris; shin; global games; policy; price; aggregation; social learning; dynamic adjustment; business cycle; heterogeneous agents; savings; utility; aiyagari; steady state; krusell; smith; idiosyncratic investment risk | macroeconomics research; analytical tools; analysis; endogenous growth; coordintation; incomplete markets; technolgy; distribution; employment; intellectual property rights; bounded rationality; demographics; complementarities; amplification; recursive equilibria; uncertainty; morris; shin; global games; policy; price; aggregation; social learning; dynamic adjustment; business cycle; heterogeneous agents; savings; utility; aiyagari; steady state; krusell; smith; idiosyncratic investment risk | macroeconomics research | macroeconomics research | analytical tools | analytical tools | analysis | analysis | endogenous growth | endogenous growth | coordintation | coordintation | incomplete markets | incomplete markets | technolgy | technolgy | distribution | distribution | employment | employment | intellectual property rights | intellectual property rights | bounded rationality | bounded rationality | demographics | demographics | complementarities | complementarities | amplification | amplification | recursive equilibria | recursive equilibria | uncertainty | uncertainty | morris | morris | shin | shin | global games | global games | policy | policy | price | price | aggregation | aggregation | social learning | social learning | dynamic adjustment | dynamic adjustment | business cycle | business cycle | heterogeneous agents | heterogeneous agents | savings | savings | utility | utility | aiyagari | aiyagari | steady state | steady state | krusell | krusell | smith | smith | idiosyncratic investment risk | idiosyncratic investment risk | growth | growth | fluctuations | fluctuations | heterogeneity | heterogeneity | optimal fiscal policy | optimal fiscal policy | time inconsistency | time inconsistency | reputation | reputation | information | information | coordination games | coordination games

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

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Castle Place, Belfast. Castle Place, Belfast.

Description

Subjects

tram | tram | belfast | belfast | northernireland | northernireland | bustle | bustle | ulster | ulster | countyantrim | countyantrim | glassnegative | glassnegative | monkeybrand | monkeybrand | robertfrench | robertfrench | williamlawrence | williamlawrence | nationallibraryofireland | nationallibraryofireland | castleplace | castleplace | lawrencecollection | lawrencecollection | brookessoap | brookessoap | cantrellcochrane | cantrellcochrane | cramerco | cramerco | lawrencephotographicstudio | lawrencephotographicstudio | thelawrencephotographcollection | thelawrencephotographcollection | dmblbit | dmblbit | seggonsphotographicstudio | seggonsphotographicstudio | jrobbcompany | jrobbcompany

License

No known copyright restrictions

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15.279 Management Communication for Undergraduates (MIT) 15.279 Management Communication for Undergraduates (MIT)

Description

This is a required seminar for Management Science majors to develop the writing, speaking, teamwork, and interpersonal communication skills necessary for managers. Students learn communication principles, strategies, and methods through discussions, exercises, examples, and cases. Assignments include writing memos and business letters, and giving oral presentations in labs outside of class. A major project is the production of a team report and presentation on a topic of interest to a managerial audience. This is a required seminar for Management Science majors to develop the writing, speaking, teamwork, and interpersonal communication skills necessary for managers. Students learn communication principles, strategies, and methods through discussions, exercises, examples, and cases. Assignments include writing memos and business letters, and giving oral presentations in labs outside of class. A major project is the production of a team report and presentation on a topic of interest to a managerial audience.

Subjects

Management | Management | Communication | Communication | Oral presentation | Oral presentation | Teamwork | Teamwork | Communications | Communications | Presentations | Presentations | writing | writing | teamwork | teamwork | grammar | grammar | usage | usage | displays | displays | visual information | visual information | graphics | graphics | conversation | conversation | management and business communication | management and business communication

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

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1.00 Introduction to Computers and Engineering Problem Solving (MIT) 1.00 Introduction to Computers and Engineering Problem Solving (MIT)

Description

This course teaches fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is focused on object-oriented software design and development. Assignments cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. The Java programming language is used. This course teaches fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is focused on object-oriented software design and development. Assignments cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. The Java programming language is used.

Subjects

computer | computer | engineering | engineering | problem solving | problem solving | software | software | software development | software development | object oriented | object oriented | programming | programming | graphical user interface | graphical user interface | numerical methods | numerical methods | data structures | data structures | sorting | sorting | searching | searching | computer graphics | computer graphics | Java | Java | C | C | C++ | C++

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

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1.00 Introduction to Computers and Engineering Problem Solving (MIT) 1.00 Introduction to Computers and Engineering Problem Solving (MIT)

Description

This course examines fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is placed on object-oriented software design and development. Students engage in active learning using laptop computers (available on loan). Assignments cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. The Java® programming language is used. This course examines fundamental software development and computational methods for engineering, scientific and managerial applications. Emphasis is placed on object-oriented software design and development. Students engage in active learning using laptop computers (available on loan). Assignments cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. The Java® programming language is used.

Subjects

computer | computer | engineering | engineering | problem solving | problem solving | software | software | software development | software development | object oriented | object oriented | programming | programming | graphical user interface | graphical user interface | numerical methods | numerical methods | data structures | data structures | sorting | sorting | searching | searching | computer graphics | computer graphics | Java | Java | C | C | C++ | C++

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

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15.075 Applied Statistics (MIT) 15.075 Applied Statistics (MIT)

Description

This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra. We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material. This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra. We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.

Subjects

data analysis | data analysis | multiple regression | multiple regression | analysis of variance | analysis of variance | multivariate analysis | multivariate analysis | data mining | data mining | probability | probability | collecting data | collecting data | sampling distributions | sampling distributions | inference | inference | linear regression | linear regression | ANOVA | ANOVA | nonparametric methods | nonparametric methods | polls | polls | surveys | surveys | statistics | statistics | management science | management science | finance | finance | statistical graphics | statistical graphics | estimation | estimation | hypothesis testing | hypothesis testing | logistic regression | logistic regression | contingency tables | contingency tables | forecasting | forecasting | factor analysis | factor analysis

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

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MAS.963 Special Topics: Computational Camera and Photography (MIT) MAS.963 Special Topics: Computational Camera and Photography (MIT)

Description

A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information

Subjects

signal processing; applied optics; Computer graphics; computer vision; online photo; digital photography; digital imaging; visual art image processing | signal processing; applied optics; Computer graphics; computer vision; online photo; digital photography; digital imaging; visual art image processing | image sensor | image sensor | image reconstruction | image reconstruction | medical imaging | medical imaging | mblog | mblog | biomimetics | biomimetics | lens | lens | spectrum | spectrum | multi-spectral | multi-spectral | 3D imaging | 3D imaging | thermal imaging | thermal imaging | high-speed imaging | high-speed imaging | polarization | polarization

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

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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

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SP.776 Design for Demining (MIT) SP.776 Design for Demining (MIT)

Description

Humanitarian Demining is the process of detecting, removing and disposing of landmines. Millions of landmines are buried in more than 80 countries resulting in 20,000 civilian victims every year. MIT Design for Demining is a design course that spans the entire product design and development process from identification of needs and idea generation to prototyping and blast testing to manufacture and deployment. Technical, business and customer aspects are addressed. Students learn about demining while they design, develop and deliver devices to aid the demining community. Past students have invented or improved hand tools, protective gear, safety equipment, educational graphics and teaching materials. Some tools designed in previous years are in use worldwide in the thousands. Course work is Humanitarian Demining is the process of detecting, removing and disposing of landmines. Millions of landmines are buried in more than 80 countries resulting in 20,000 civilian victims every year. MIT Design for Demining is a design course that spans the entire product design and development process from identification of needs and idea generation to prototyping and blast testing to manufacture and deployment. Technical, business and customer aspects are addressed. Students learn about demining while they design, develop and deliver devices to aid the demining community. Past students have invented or improved hand tools, protective gear, safety equipment, educational graphics and teaching materials. Some tools designed in previous years are in use worldwide in the thousands. Course work is

Subjects

humanitarian demining | humanitarian demining | landmines | landmines | landmine detection | landmine detection | landmine removal | landmine removal | landmine disposal | landmine disposal | landmines in 80 countries | landmines in 80 countries | 20 | 000 civilian victims per year | 20 | 000 civilian victims per year | MIT Design for Demining | MIT Design for Demining | product design | product design | development process | development process | identification of needs | identification of needs | idea generation | idea generation | prototyping | prototyping | blast testing | blast testing | manufacture | manufacture | deployment | deployment | demining community | demining community | hand tools | hand tools | protective gear | protective gear | safety equipment | safety equipment | educational graphics | educational graphics | teaching materials | teaching materials | field trip | field trip | US Army base | US Army base | demining training | demining training

License

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1.00 Introduction to Computers and Engineering Problem Solving (MIT) 1.00 Introduction to Computers and Engineering Problem Solving (MIT)

Description

This course presents fundamental software development and computational methods for engineering and scientific applications. Object-oriented software design and development is the focus of the course. Weekly programming problems cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. Emphasis is on developing techniques for solving problems in engineering, science, management, and planning. The Java® programming language is used. The course is worth 3 Engineering Design Points.Technical RequirementsAny number of development tools can be used to compile and run the .java files found on this course site. Please refer to the course materials for any specific instructions or recomm This course presents fundamental software development and computational methods for engineering and scientific applications. Object-oriented software design and development is the focus of the course. Weekly programming problems cover programming concepts, graphical user interfaces, numerical methods, data structures, sorting and searching, computer graphics and selected advanced topics. Emphasis is on developing techniques for solving problems in engineering, science, management, and planning. The Java® programming language is used. The course is worth 3 Engineering Design Points.Technical RequirementsAny number of development tools can be used to compile and run the .java files found on this course site. Please refer to the course materials for any specific instructions or recomm

Subjects

computer | computer | engineering | engineering | problem solving | problem solving | software | software | software development | software development | object oriented | object oriented | programming | programming | graphical user interface | graphical user interface | numerical methods | numerical methods | data structures | data structures | sorting | sorting | searching | searching | computer graphics | computer graphics | Java | Java | C | C | C++ | C++

License

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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

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4.491 Form-Finding and Structural Optimization: Gaudi Workshop (MIT) 4.491 Form-Finding and Structural Optimization: Gaudi Workshop (MIT)

Description

Inspired by the work of the architect Antoni Gaudi, this research workshop will explore three-dimensional problems in the static equilibrium of structural systems. Through an interdisciplinary collaboration between computer science and architecture, we will develop design tools for determining the form of three-dimensional structural systems under a variety of loads. The goal of the workshop is to develop real-time design and analysis tools which will be useful to architects and engineers in the form-finding of efficient three-dimensional structural systems. Inspired by the work of the architect Antoni Gaudi, this research workshop will explore three-dimensional problems in the static equilibrium of structural systems. Through an interdisciplinary collaboration between computer science and architecture, we will develop design tools for determining the form of three-dimensional structural systems under a variety of loads. The goal of the workshop is to develop real-time design and analysis tools which will be useful to architects and engineers in the form-finding of efficient three-dimensional structural systems.

Subjects

structures | structures | statics | statics | architecture | architecture | Gaudi | Gaudi | Barcelona | Barcelona | computer science | computer science | structural systems | structural systems | computer modeling | computer modeling | advanced dynamics | advanced dynamics | form-finding | form-finding | shaping structures | shaping structures | mesh generation | mesh generation | procedural methods for creating structural elements | procedural methods for creating structural elements | physical simulation procedures | physical simulation procedures | interactive design tools | interactive design tools | structural analysis | structural analysis | computer graphics | computer graphics | mathematics of nodal systems | mathematics of nodal systems

License

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MAS.531 Computational Camera and Photography (MIT) MAS.531 Computational Camera and Photography (MIT)

Description

Includes audio/video content: AV lectures. A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aest Includes audio/video content: AV lectures. A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aest

Subjects

digital photography | digital photography | digital imaging | digital imaging | image processing | image processing | applied optics | applied optics | computer graphics | computer graphics | computer vision | computer vision

License

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1.00 Introduction to Computers and Engineering Problem Solving (MIT) 1.00 Introduction to Computers and Engineering Problem Solving (MIT)

Description

This course presents the fundamentals of object-oriented software design and development, computational methods and sensing for engineering, and scientific and managerial applications. It cover topics, including design of classes, inheritance, graphical user interfaces, numerical methods, streams, threads, sensors, and data structures. Students use Java® programming language to complete weekly software assignments. How is 1.00 different from other intro programming courses offered at MIT? 1.00 is a first course in programming. It assumes no prior experience, and it focuses on the use of computation to solve problems in engineering, science and management. The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where t This course presents the fundamentals of object-oriented software design and development, computational methods and sensing for engineering, and scientific and managerial applications. It cover topics, including design of classes, inheritance, graphical user interfaces, numerical methods, streams, threads, sensors, and data structures. Students use Java® programming language to complete weekly software assignments. How is 1.00 different from other intro programming courses offered at MIT? 1.00 is a first course in programming. It assumes no prior experience, and it focuses on the use of computation to solve problems in engineering, science and management. The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where t

Subjects

computer | computer | engineering | engineering | problem solving | problem solving | software | software | software development | software development | programming | programming | graphical user interface | graphical user interface | numerical methods | numerical methods | data structures | data structures | sorting | sorting | searching | searching | computer graphics | computer graphics | Java | Java

License

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9.520 Statistical Learning Theory and Applications (MIT) 9.520 Statistical Learning Theory and Applications (MIT)

Description

This course is for upper-level graduate students who are planning careers in computational neuroscience. This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification, and Bioinformatics. The final projects, hands-on applications, and exercises are designed to illustrate the rapidly increasing practical uses This course is for upper-level graduate students who are planning careers in computational neuroscience. This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification, and Bioinformatics. The final projects, hands-on applications, and exercises are designed to illustrate the rapidly increasing practical uses

Subjects

supervised learning | supervised learning | statistical learning | statistical learning | multivariate function | multivariate function | Support Vector Machines | Support Vector Machines | regression | regression | classification | classification | VC theory | VC theory | computer vision | computer vision | computer graphics | computer graphics | bioinformatics | bioinformatics

License

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9.520 Statistical Learning Theory and Applications (MIT) 9.520 Statistical Learning Theory and Applications (MIT)

Description

Focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. Develops basic tools such as Regularization including Support Vector Machines for regression and classification. Derives generalization bounds using both stability and VC theory. Discusses topics such as boosting and feature selection. Examines applications in several areas: computer vision, computer graphics, text classification and bioinformatics. Final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject. Focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. Develops basic tools such as Regularization including Support Vector Machines for regression and classification. Derives generalization bounds using both stability and VC theory. Discusses topics such as boosting and feature selection. Examines applications in several areas: computer vision, computer graphics, text classification and bioinformatics. Final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject.

Subjects

supervised learning | supervised learning | statistical learning | statistical learning | multivariate function | multivariate function | Support Vector Machines | Support Vector Machines | regression | regression | classification | classification | VC theory | VC theory | computer vision | computer vision | computer graphics | computer graphics | bioinformatics | bioinformatics

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

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9.357 Special Topics in Vision Science (MIT) 9.357 Special Topics in Vision Science (MIT)

Description

An advanced seminar on issues of current interest in human and machine vision. Topics vary from year to year. This year, the class will involve studying the perception of materials. Participants discuss current literature as well as their ongoing research. Topics are tackled from multiple standpoints, including optics, psychophysics, computer graphics and computer vision. An advanced seminar on issues of current interest in human and machine vision. Topics vary from year to year. This year, the class will involve studying the perception of materials. Participants discuss current literature as well as their ongoing research. Topics are tackled from multiple standpoints, including optics, psychophysics, computer graphics and computer vision.

Subjects

vision | vision | perception | perception | materials | materials | optics | optics | psychophysics | psychophysics | computer graphics | computer graphics | computer vision | computer vision

License

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18.337J Parallel Computing (MIT) 18.337J Parallel Computing (MIT)

Description

This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language, a free, open-source, high-performance dynamic programming language for technical computing. This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language, a free, open-source, high-performance dynamic programming language for technical computing.

Subjects

cloud computing | cloud computing | dense linear algebra | dense linear algebra | sparse linear algebra | sparse linear algebra | N-body problems | N-body problems | multigrid | multigrid | fast-multipole | fast-multipole | wavelets | wavelets | Fourier transforms | Fourier transforms | partitioning | partitioning | mesh generation | mesh generation | applications oriented architecture | applications oriented architecture | parallel programming paradigms | parallel programming paradigms | MPI | MPI | data parallel systems | data parallel systems | Star-P | Star-P | parallel Python | parallel Python | parallel Matlab | parallel Matlab | graphics processors | graphics processors | virtualization | virtualization | caches | caches | vector processors | vector processors | VHLLs | VHLLs | Very High Level Languages | Very High Level Languages | Julia programming language | Julia programming language | distributed parallel execution | distributed parallel execution

License

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