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Readme file for Computer Science Concepts

Description

This readme file contains details of links to all the Computer Science Concepts module's material held on Jorum and information about the module as well.Subjects

ukoer | strings lecture | induction and recursion lecture | induction lecture | recursion lecture | complexity lecture | languages lecture | computer sciences concepts test | computer science concepts test | computer science concepts assignment | computer science concepts practical | introduction | computer science concepts | computer science concept | computer science | strings and languages | strings and language | string and languages | string and language | string | language | languages | finite automata | automata | finite | push down automata | push down | prolog | data structures and algorithms | data structure and algorithms | data structures and algorithm | data structure and algorithm | data structures | data structure | algorithms | algorithm | revision exercises | revision | induction and recursion | induction | recursion | turing machines | turing machine | turing | machine | machines | complexity | grammar | grammar and languages | grammar and language | introduction lecture | computer science concepts lecture | computer science concept lecture | computer science lecture | strings and languages lecture | strings and language lecture | string and languages lecture | string and language lecture | string lecture | language lecture | finite automata lecture | automata lecture | finite lecture | push down automata lecture | push down lecture | prolog lecture | data structures and algorithms lecture | data structure and algorithms lecture | data structures and algorithm lecture | data structure and algorithm lecture | data structures lecture | data structure lecture | algorithms lecture | algorithm lecture | revision exercises lecture | revision lecture | turing machines lecture | turing machine lecture | turing lecture | machine lecture | machines lecture | computer science class test | computer science concept class test | computer science concepts class test | strings and languages class test | strings and language class test | string and languages class test | string and language class test | string class test | language class test | languages class test | introduction class test | grammar lecture | grammar and languages lecture | grammar and language lecture | computer science assignment | computer science concept assignment | strings and languages assignment | strings and language assignment | string and languages assignment | string and language assignment | string assignment | language assignment | languages assignment | finite automata class test | automata class test | finite class test | finite automata assignment | automata assignment | finite assignment | push down automata class test | push down class test | push down automata assignment | push down assignment | prolog class test | data structures and algorithms class test | data structure and algorithms class test | data structures and algorithm class test | data structure and algorithm class test | data structures class test | data structure class test | algorithms class test | algorithm class test | computer science practical | computer science concept practical | data structures and algorithms practical | data structure and algorithms practical | data structures and algorithm practical | data structure and algorithm practical | data structures practical | data structure practical | algorithms practical | algorithm practical | revision exercises class test | revision class test | induction and recursion class test | induction class test | recursion class test | induction and recursion assignment | induction assignment | recursion assignment | turing machines class test | turing machine class test | turing class test | machine class test | machines class test | turing machines assignment | turing machine assignment | turing assignment | machine assignment | machines assignment | complexity class test | grammar class test | grammar and languages class test | grammar and language class test | Computer science | I100License

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See all metadataComputer Science Concepts - Data structures and algorithms

Description

This lecture forms part of the "Data structures and algorithms" topic of the Computer Science Concepts module.Subjects

ukoer | computer science | computer science concept | computer science concepts | data structures and algorithms | data structure and algorithms | data structures and algorithm | data structure and algorithm | data structures | data structure | algorithms | algorithm | computer science lecture | computer science concept lecture | computer science concepts lecture | data structures and algorithms lecture | data structure and algorithms lecture | data structures and algorithm lecture | data structure and algorithm lecture | data structures lecture | data structure lecture | algorithms lecture | algorithm lecture | Computer science | I100License

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See all metadataComputer Science Concepts - Data structures and algorithms

Description

This class test forms part of the "Data structures and algorithms" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts test | computer science | computer science concept | computer science concepts | data structures and algorithms | data structure and algorithms | data structures and algorithm | data structure and algorithm | data structures | data structure | algorithms | algorithm | computer science class test | computer science concept class test | computer science concepts class test | data structures and algorithms class test | data structure and algorithms class test | data structures and algorithm class test | data structure and algorithm class test | data structures class test | data structure class test | algorithms class test | algorithm class test | Computer science | I100License

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See all metadataComputer Science Concepts - Data structures and algorithms

Description

This class test forms part of the "Data structures and algorithms" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts test | computer science | computer science concept | computer science concepts | data structures and algorithms | data structure and algorithms | data structures and algorithm | data structure and algorithm | data structures | data structure | algorithms | algorithm | computer science class test | computer science concept class test | computer science concepts class test | data structures and algorithms class test | data structure and algorithms class test | data structures and algorithm class test | data structure and algorithm class test | data structures class test | data structure class test | algorithms class test | algorithm class test | Computer science | I100License

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See all metadataComputer Science Concepts - Data structures and algorithms

Description

This practical forms part of the "Data structures and algorithms" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts practical | computer science | computer science concept | computer science concepts | data structures and algorithms | data structure and algorithms | data structures and algorithm | data structure and algorithm | data structures | data structure | algorithms | algorithm | computer science practical | computer science concept practical | data structures and algorithms practical | data structure and algorithms practical | data structures and algorithm practical | data structure and algorithm practical | data structures practical | data structure practical | algorithms practical | algorithm practical | Computer science | I100License

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See all metadata6.851 Advanced Data Structures (MIT) 6.851 Advanced Data Structures (MIT)

Description

Data structures play a central role in modern computer science. You interact with data structures much more often than with algorithms (think of Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course will cover major results and current directions of research in data structures. Data structures play a central role in modern computer science. You interact with data structures much more often than with algorithms (think of Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course will cover major results and current directions of research in data structures.Subjects

dynamic optimality | dynamic optimality | geometric data structures | geometric data structures | strings | strings | integers | integers | dictionaries | dictionaries | dynamic graphs | dynamic graphs | temporal data structures | temporal data structures | external memory | external memory | cache-oblivious | cache-oblivious | succinct data structures | succinct data structuresLicense

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.htmSite sourced from

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See all metadata6.837 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 hardwareLicense

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.htmSite sourced from

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See all metadata6.851 Advanced Data Structures (MIT)

Description

Data structures play a central role in modern computer science. You interact with data structures much more often than with algorithms (think of Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course will cover major results and current directions of research in data structures.Subjects

dynamic optimality | geometric data structures | strings | integers | dictionaries | dynamic graphs | temporal data structures | external memory | cache-oblivious | succinct data structuresLicense

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.htmSite sourced from

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See all metadata6.851 Advanced Data Structures (MIT)

Description

Data structures play a central role in modern computer science. You interact with data structures much more often than with algorithms (think of Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course will cover major results and current directions of research in data structures.Subjects

dynamic optimality | geometric data structures | strings | integers | dictionaries | dynamic graphs | temporal data structures | external memory | cache-oblivious | succinct data structuresLicense

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.htmSite sourced from

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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.htmSite sourced from

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See all metadataDescription

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.htmSite sourced from

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See all metadata6.094 Introduction to MATLAB® (MIT) 6.094 Introduction to MATLAB® (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. 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.Subjects

matlab | matlab | simulink | simulink | matlab programming | matlab programming | variables | variables | plotting | plotting | scripts | scripts | functions | functions | flow control | flow control | linear algebra | linear algebra | polynomials | polynomials | optimization | optimization | differential equations | differential equations | ode | ode | probability | probability | statistics | statistics | data structures | data structures | images | images | animation | animation | debugging | debugging | symbolic math | symbolic math | toolboxes | toolboxes | scope | scope | function block | function block | nervous system | nervous systemLicense

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.htmSite sourced from

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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 recommSubjects

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.htmSite sourced from

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See all metadata6.854J Advanced Algorithms (MIT) 6.854J Advanced Algorithms (MIT)

Description

6.854J is a first-year graduate course in algorithms, continuing where 6.046J left off. The course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Topics include: data structures, network flows, linear programming, computational geometry, approximation algorithms. 6.854J is a first-year graduate course in algorithms, continuing where 6.046J left off. The course emphasizes fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Topics include: data structures, network flows, linear programming, computational geometry, approximation algorithms.Subjects

algorithm design and analysis | algorithm design and analysis | algorithms | algorithms | fundamental algorithms | fundamental algorithms | advanced methods of algorithmic design | advanced methods of algorithmic design | analysis | analysis | implementation | implementation | data structures | data structures | network flows | network flows | linear programming | linear programming | computational geometry | computational geometry | approximation algorithms | approximation algorithms | algorithmic design | algorithmic design | algorithmic analysis | algorithmic analysis | string algorithms | string algorithms | maximum flows | maximum flows | online algorithms | online algorithms | scheduling | scheduling | external memory algorithms | external memory algorithms | 6.854 | 6.854 | 18.415 | 18.415License

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.htmSite sourced from

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See all metadata18.S997 Introduction To MATLAB Programming (MIT) 18.S997 Introduction To MATLAB Programming (MIT)

Description

Includes audio/video content: AV lectures. This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB® in particular. Includes audio/video content: AV lectures. This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB® in particular.Subjects

MATLAB | programming | MATLAB | programming | variables | variables | plotting | plotting | scripts | scripts | functions | functions | flow control | flow control | statistics | statistics | data structures | data structures | images | images | vectors | vectors | matrices | matrices | root-finding | root-finding | Newton's Method | Newton's Method | Secant Method | Secant Method | Basins of Attraction | Basins of Attraction | Conway Game of Life | Conway Game of Life | Game of Life | Game of Life | vectorization | vectorization | debugging | debugging | scope | scope | function block | function blockLicense

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.htmSite sourced from

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See all metadata6.006 Introduction to Algorithms (MIT) 6.006 Introduction to Algorithms (MIT)

Description

Includes audio/video content: AV lectures. This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems. Includes audio/video content: AV lectures. This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.Subjects

algorithms | algorithms | data structures | data structures | algorithm performance | algorithm performance | algorithm analysis | algorithm analysis | sorting | sorting | trees | trees | hashing | hashing | numerics | numerics | graphs | graphs | shortest paths | shortest paths | dynamic programming | dynamic programming | Python | PythonLicense

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.htmSite sourced from

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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 tSubjects

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 | JavaLicense

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.htmSite sourced from

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This course covers concepts of computation used in analysis of engineering systems. It includes the following topics: data structures, relational database representations of engineering data, algorithms for the solution and optimization of engineering system designs (greedy, dynamic programming, branch and bound, graph algorithms, nonlinear optimization), and introduction to complexity analysis. Object-oriented, efficient implementations of algorithms are emphasized. This course covers concepts of computation used in analysis of engineering systems. It includes the following topics: data structures, relational database representations of engineering data, algorithms for the solution and optimization of engineering system designs (greedy, dynamic programming, branch and bound, graph algorithms, nonlinear optimization), and introduction to complexity analysis. Object-oriented, efficient implementations of algorithms are emphasized.Subjects

databases | databases | data structures | data structures | divide and conquer algorithm | divide and conquer algorithm | greedy algorithm | greedy algorithm | dynamic programming | dynamic programming | branch and bound | branch and bound | linear optimization | linear optimization | nonlinear optimization | nonlinear optimization | approximate queues | approximate queues | network designs | network designsLicense

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.htmSite sourced from

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See all metadata1.124J 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 | 13.470License

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.htmSite sourced from

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See all metadata6.094 Introduction to MATLAB (MIT) 6.094 Introduction to MATLAB (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with students doing sample MATLAB problems in real time. Problem-based MATLAB assignments are given which require significant time on MATLAB. 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. Acknowledgements The 6.094 course materials were developed by Danilo Šćepanović, Sourav R. Dey, Ankit Patel, and Patrick Ho. This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with students doing sample MATLAB problems in real time. Problem-based MATLAB assignments are given which require significant time on MATLAB. 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. Acknowledgements The 6.094 course materials were developed by Danilo Šćepanović, Sourav R. Dey, Ankit Patel, and Patrick Ho.Subjects

introduction to MATLAB | introduction to MATLAB | scripts | scripts | making variables | making variables | manipulating variables | manipulating variables | functions | functions | flow control | flow control | line plots | line plots | surface plots | surface plots | vectorization | vectorization | linear algebra | linear algebra | optimization | optimization | differential equations | differential equations | data structures | data structures | debugging | debugging | animation | animation | symbolic math | symbolic math | Simulink | Simulink | file input/output | file input/output | graphical user interfaces | graphical user interfacesLicense

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.htmSite sourced from

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This course will provide a gentle introduction to programming using Python™ for highly motivated students with little or no prior experience in programming computers. 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 course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course will provide a gentle introduction to programming using Python™ for highly motivated students with little or no prior experience in programming computers. 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 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.Subjects

Python | Python | introduction to programming | introduction to programming | how to think like a computer scientist | how to think like a computer scientist | control flow | control flow | lists | lists | strings | strings | tuples | tuples | objects | objects | mutability | mutability | scope | scope | dictionaries | dictionaries | web search | web search | recursion | recursion | branching and repetition | branching and repetition | structuring programs | structuring programs | debugging programs | debugging programs | data structures | data structures | teamwork | teamwork | modularity | modularity | incremental programming | incremental programmingLicense

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.htmSite sourced from

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See all metadata6.854J Advanced Algorithms (MIT) 6.854J Advanced Algorithms (MIT)

Description

This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures. This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures.Subjects

amortization | amortization | randomization | randomization | fingerprinting | fingerprinting | word-level parallelism | word-level parallelism | bit scaling | bit scaling | dynamic programming | dynamic programming | network flow | network flow | linear programming | linear programming | fixed-parameter algorithms | fixed-parameter algorithms | approximation algorithms | approximation algorithms | string algorithms | string algorithms | network optimization | network optimization | parallel algorithms | parallel algorithms | computational geometry | computational geometry | online algorithms | online algorithms | external memory | external memory | external cache | external cache | external streaming | external streaming | data structures | data structuresLicense

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.htmSite sourced from

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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 hardwareLicense

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.htmSite sourced from

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See all metadata6.856J Randomized Algorithms (MIT) 6.856J Randomized Algorithms (MIT)

Description

This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimum cuts); geometric algorithms (convex hulls, linear programming in fixed or arbitrary dimension); approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms. This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimum cuts); geometric algorithms (convex hulls, linear programming in fixed or arbitrary dimension); approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.Subjects

Randomized Algorithms | Randomized Algorithms | algorithms | algorithms | efficient in time and space | efficient in time and space | randomization | randomization | computational problems | computational problems | data structures | data structures | graph algorithms | graph algorithms | optimization | optimization | geometry | geometry | Markov chains | Markov chains | sampling | sampling | estimation | estimation | geometric algorithms | geometric algorithms | parallel and distributed algorithms | parallel and distributed algorithms | parallel and ditributed algorithm | parallel and ditributed algorithm | parallel and distributed algorithm | parallel and distributed algorithm | random sampling | random sampling | random selection of witnesses | random selection of witnesses | symmetry breaking | symmetry breaking | randomized computational models | randomized computational models | hash tables | hash tables | skip lists | skip lists | minimum spanning trees | minimum spanning trees | shortest paths | shortest paths | minimum cuts | minimum cuts | convex hulls | convex hulls | linear programming | linear programming | fixed dimension | fixed dimension | arbitrary dimension | arbitrary dimension | approximate counting | approximate counting | parallel algorithms | parallel algorithms | online algorithms | online algorithms | derandomization techniques | derandomization techniques | probabilistic analysis | probabilistic analysis | computational number theory | computational number theory | simplicity | simplicity | speed | speed | design | design | basic probability theory | basic probability theory | application | application | randomized complexity classes | randomized complexity classes | game-theoretic techniques | game-theoretic techniques | Chebyshev | Chebyshev | moment inequalities | moment inequalities | limited independence | limited independence | coupon collection | coupon collection | occupancy problems | occupancy problems | tail inequalities | tail inequalities | Chernoff bound | Chernoff bound | conditional expectation | conditional expectation | probabilistic method | probabilistic method | random walks | random walks | algebraic techniques | algebraic techniques | probability amplification | probability amplification | sorting | sorting | searching | searching | combinatorial optimization | combinatorial optimization | approximation | approximation | counting problems | counting problems | distributed algorithms | distributed algorithms | 6.856 | 6.856 | 18.416 | 18.416License

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.htmSite sourced from

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See all metadata15.082J Network Optimization (MIT) 15.082J Network Optimization (MIT)

Description

15.082J/6.855J/ESD.78J is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems. 15.082J/6.855J/ESD.78J is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems.Subjects

15.082 | 15.082 | 6.855 | 6.855 | ESD.78 | ESD.78 | network models | network models | network design | network design | maximum flow algorithm | maximum flow algorithm | minimum cost flow | minimum cost flow | shortest path algorithm | shortest path algorithm | algorithm efficiency | algorithm efficiency | preflow push algorithm | preflow push algorithm | data structures | data structuresLicense

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.htmSite sourced from

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