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6.042J Mathematics for Computer Science (MIT) 6.042J Mathematics for Computer Science (MIT)

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This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science). This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science).Subjects

mathematical definitions | mathematical definitions | proofs and applicable methods | proofs and applicable methods | formal logic notation | formal logic notation | proof methods | proof methods | induction | induction | well-ordering | well-ordering | sets | sets | relations | relations | elementary graph theory | elementary graph theory | integer congruences | integer congruences | asymptotic notation and growth of functions | asymptotic notation and growth of functions | permutations and combinations | counting principles | permutations and combinations | counting principles | discrete probability | discrete probability | recursive definition | recursive definition | structural induction | structural induction | state machines and invariants | state machines and invariants | recurrences | recurrences | generating functions | generating functions | permutations and combinations | permutations and combinations | counting principles | counting principles | discrete mathematics | discrete mathematics | computer science | computer scienceLicense

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See all metadata6.042J Mathematics for Computer Science (MIT) 6.042J Mathematics for Computer Science (MIT)

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This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science). This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science).Subjects

mathematical definitions | mathematical definitions | proofs and applicable methods | proofs and applicable methods | formal logic notation | formal logic notation | proof methods | proof methods | induction | induction | well-ordering | well-ordering | sets | sets | relations | relations | elementary graph theory | elementary graph theory | integer congruences | integer congruences | asymptotic notation and growth of functions | asymptotic notation and growth of functions | permutations and combinations | counting principles | permutations and combinations | counting principles | discrete probability | discrete probability | recursive definition | recursive definition | structural induction | structural induction | state machines and invariants | state machines and invariants | recurrences | recurrences | generating functions | generating functions | permutations and combinations | permutations and combinations | counting principles | counting principles | discrete mathematics | discrete mathematics | computer science | computer scienceLicense

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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Professor Peter Donnelly tells us how genetics helps us to understand common diseases and develop new drugs. Understanding which variations in our DNA affect susceptibility to diseases can provide new insights into the disease process and lead to new treatments. Professor Peter Donnelly leads large collaborative human genetic studies, and his group develops and applies statistical methods to extract maximal information from the large datasets generated by genomic studies. Professor Peter Donnelly tells us how genetics helps us to understand common diseases and develop new drugs. Understanding which variations in our DNA affect susceptibility to diseases can provide new insights into the disease process and lead to new treatments. Professor Peter Donnelly leads large collaborative human genetic studies, and his group develops and applies statistical methods to extract maximal information from the large datasets generated by genomic studies.Subjects

recombination | recombination | genome-wide association study (GWAS) | genome-wide association study (GWAS) | Statistical Genetics | Statistical Genetics | population genetics | population genetics | recombination | genome-wide association study (GWAS) | Statistical Genetics | population genetics | recombination | genome-wide association study (GWAS) | Statistical Genetics | population geneticsLicense

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See all metadata6.042J Mathematics for Computer Science (MIT) 6.042J Mathematics for Computer Science (MIT)

Description

This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science). This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds: Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting Discrete Probability Theory A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science).Subjects

mathematical definitions | mathematical definitions | proofs and applicable methods | proofs and applicable methods | formal logic notation | formal logic notation | proof methods | proof methods | induction | induction | well-ordering | well-ordering | sets | sets | relations | relations | elementary graph theory | elementary graph theory | integer congruences | integer congruences | asymptotic notation and growth of functions | asymptotic notation and growth of functions | permutations and combinations | counting principles | permutations and combinations | counting principles | discrete probability | discrete probability | recursive definition | recursive definition | structural induction | structural induction | state machines and invariants | state machines and invariants | recurrences | recurrences | generating functions | generating functions | permutations and combinations | permutations and combinations | counting principles | counting principles | discrete mathematics | discrete mathematics | computer science | computer scienceLicense

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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Professor Peter Donnelly tells us how genetics helps us to understand common diseases and develop new drugs. Understanding which variations in our DNA affect susceptibility to diseases can provide new insights into the disease process and lead to new treatments. Professor Peter Donnelly leads large collaborative human genetic studies, and his group develops and applies statistical methods to extract maximal information from the large datasets generated by genomic studies. Professor Peter Donnelly tells us how genetics helps us to understand common diseases and develop new drugs. Understanding which variations in our DNA affect susceptibility to diseases can provide new insights into the disease process and lead to new treatments. Professor Peter Donnelly leads large collaborative human genetic studies, and his group develops and applies statistical methods to extract maximal information from the large datasets generated by genomic studies.Subjects

recombination | recombination | genome-wide association study (GWAS) | genome-wide association study (GWAS) | Statistical Genetics | Statistical Genetics | population genetics | population genetics | recombination | genome-wide association study (GWAS) | Statistical Genetics | population genetics | recombination | genome-wide association study (GWAS) | Statistical Genetics | population geneticsLicense

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Directed evolution has been used to produce enzymes with many unique properties. The technique of directed evolution comprises two essential steps: mutagenesis of the gene encoding the enzyme to produce a library of variants, and selection of a particular variant based on its desirable catalytic properties. In this course we will examine what kinds of enzymes are worth evolving and the strategies used for library generation and enzyme selection. We will focus on those enzymes that are used in the synthesis of drugs and in biotechnological applications. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current Directed evolution has been used to produce enzymes with many unique properties. The technique of directed evolution comprises two essential steps: mutagenesis of the gene encoding the enzyme to produce a library of variants, and selection of a particular variant based on its desirable catalytic properties. In this course we will examine what kinds of enzymes are worth evolving and the strategies used for library generation and enzyme selection. We will focus on those enzymes that are used in the synthesis of drugs and in biotechnological applications. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about currentSubjects

evolution | evolution | biocatalyst | biocatalyst | mutation | mutation | library | library | recombination | recombination | directed evolution | directed evolution | enzyme | enzyme | point mutation | point mutation | mutagenesis | mutagenesis | DNA | DNA | gene | gene | complementation | complementation | affinity | affinity | phage | phage | ribosome display | ribosome display | yeast surface display | yeast surface display | bacterial cell surface display | bacterial cell surface display | IVC | IVC | FACS | FACS | active site | active siteLicense

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See all metadata6.042J Mathematics for Computer Science (MIT) 6.042J Mathematics for Computer Science (MIT)

Description

This course is offered to undergraduates and is an elementary discrete mathematics course oriented towards applications in computer science and engineering. Topics covered include: formal logic notation, induction, sets and relations, permutations and combinations, counting principles, and discrete probability. This course is offered to undergraduates and is an elementary discrete mathematics course oriented towards applications in computer science and engineering. Topics covered include: formal logic notation, induction, sets and relations, permutations and combinations, counting principles, and discrete probability.Subjects

Elementary discrete mathematics for computer science and engineering | Elementary discrete mathematics for computer science and engineering | mathematical definitions | mathematical definitions | proofs and applicable methods | proofs and applicable methods | formal logic notation | formal logic notation | proof methods | proof methods | induction | induction | well-ordering | well-ordering | sets | sets | relations | relations | elementary graph theory | elementary graph theory | integer congruences | integer congruences | asymptotic notation and growth of functions | asymptotic notation and growth of functions | permutations and combinations | permutations and combinations | counting principles | counting principles | discrete probability | discrete probability | recursive definition | recursive definition | structural induction | structural induction | state machines and invariants | state machines and invariants | recurrences | recurrences | generating functions | generating functions | 6.042 | 6.042 | 18.062 | 18.062License

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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See all metadata7.28 Molecular Biology (MIT) 7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized. This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.Subjects

molecular biology | molecular biology | biochemical mechanisms | biochemical mechanisms | gene expression | gene expression | evolution | evolution | prokaryotic genome | prokaryotic genome | eukaryotic genomes | eukaryotic genomes | gene regulation | gene regulation | DNA replication | DNA replication | genetic recombination | genetic recombination | RNA processing | RNA processing | translation | translation | genome | genomeLicense

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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6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models and parasitics; device sizing and logical effort; timing issues (clock skew and jitter) and active clock distribution techniques; memory architectures, circuits (sense amplifiers) and devices; testing of integrated circuits. The course employs extensive use of circuit layout and SPICE in design projects and software labs. 6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models and parasitics; device sizing and logical effort; timing issues (clock skew and jitter) and active clock distribution techniques; memory architectures, circuits (sense amplifiers) and devices; testing of integrated circuits. The course employs extensive use of circuit layout and SPICE in design projects and software labs.Subjects

digital integrated circuit | device | circuit | digital | MOS | digital integrated circuit | device | circuit | digital | MOS | digital integrated circuit | digital integrated circuit | device | device | circuit | circuit | digital | digital | MOS | MOS | Deep Sub-Micron effects | Deep Sub-Micron effects | circuit design | circuit design | logic | logic | interconnect models; parasitics | interconnect models; parasitics | device sizing | device sizing | timing | timing | clock skew | clock skew | jitter; clock distribution techniques | jitter; clock distribution techniques | memory architectures | memory architectures | circuits | circuits | sense amplifiers | sense amplifiers | SPICE | SPICE | HSPICE | HSPICE | Magic | Magic | Nanosim | Nanosim | Avanwaves | Avanwaves | device level optimization | device level optimization | interconnect models | interconnect models | parasitics | parasitics | jitter | jitter | clock distribution techniques | clock distribution techniques | CMOS inverter | CMOS inverter | combinational logic | combinational logic | sequential circuits | sequential circuitsLicense

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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6.111 covers digital design topics such as digital logic, flipflops, PALs, CPLDs, FPGAs, counters, timing, synchronization, and finite-state machines. The semester begins with lectures and problem sets, to introduce fundamental topics before students embark on lab assignments and ultimately, a digital design project. The students design and implement a final digital project of their choice, in areas such as games, music, digital filters, wireless communications, and graphics. The course relies on extensive use of Verilog® for describing and implementing digital logic designs. 6.111 covers digital design topics such as digital logic, flipflops, PALs, CPLDs, FPGAs, counters, timing, synchronization, and finite-state machines. The semester begins with lectures and problem sets, to introduce fundamental topics before students embark on lab assignments and ultimately, a digital design project. The students design and implement a final digital project of their choice, in areas such as games, music, digital filters, wireless communications, and graphics. The course relies on extensive use of Verilog® for describing and implementing digital logic designs.Subjects

digital systems laboratory | digital systems laboratory | laboratory | laboratory | digital logic | digital logic | Boolean algebra | Boolean algebra | flip-flops | flip-flops | finite-state machines | finite-state machines | FSM | FSM | microprogrammed systems | microprogrammed systems | digital abstractions | digital abstractions | digital paradigm | digital paradigm | digital oscilloscopes | digital oscilloscopes | PAL | PAL | PROM | PROM | VHDL | VHDL | digital circuit design | digital circuit design | FPGA | FPGA | counters | counters | timing | timing | synchronization | synchronization | digital filters | digital filters | wireless communications | wireless communications | verilog | verilog | combinational logic | combinational logic | simple sequential circuits | simple sequential circuits | memories | memories | configurable logic | configurable logicLicense

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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See all metadata12.864 Inference from Data and Models (MIT) 12.864 Inference from Data and Models (MIT)

Description

The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themesLinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.Standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc. The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themesLinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.Standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc.Subjects

kinematical and dynamical models | kinematical and dynamical models | Basic statistics | Basic statistics | linear algebra | linear algebra | inverse methods | inverse methods | singular value decompositions | singular value decompositions | control theory | control theory | sequential estimation | sequential estimation | Kalman filters | Kalman filters | smoothing algorithms | smoothing algorithms | adjoint/Pontryagin principle methods | adjoint/Pontryagin principle methods | model testing | model testing | stationary processes | stationary processes | Fourier methods | Fourier methods | z-transforms | z-transforms | sampling theorems | sampling theorems | spectra | spectra | multi-taper methods | multi-taper methods | coherences | coherences | filtering | filtering | quantitative combinations of models | quantitative combinations of modelsLicense

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See all metadata6.042J Mathematics for Computer Science (MIT) 6.042J Mathematics for Computer Science (MIT)

Description

Includes audio/video content: AV lectures. This subject offers an interactive introduction to discrete mathematics oriented toward computer science and engineering. The subject coverage divides roughly into thirds: Fundamental concepts of mathematics: Definitions, proofs, sets, functions, relations. Discrete structures: graphs, state machines, modular arithmetic, counting. Discrete probability theory. On completion of 6.042J, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in computer science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.Interactive site components can be found on the Unit pages in the Includes audio/video content: AV lectures. This subject offers an interactive introduction to discrete mathematics oriented toward computer science and engineering. The subject coverage divides roughly into thirds: Fundamental concepts of mathematics: Definitions, proofs, sets, functions, relations. Discrete structures: graphs, state machines, modular arithmetic, counting. Discrete probability theory. On completion of 6.042J, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in computer science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.Interactive site components can be found on the Unit pages in theSubjects

6.042 | 6.042 | 18.062 | 18.062 | formal logic notation | formal logic notation | proof methods | proof methods | induction | induction | sets | sets | relations | relations | graph theory | graph theory | integer congruences | integer congruences | asymptotic notation | asymptotic notation | growth of functions | growth of functions | permutations | permutations | combinations | combinations | counting | counting | discrete probability | discrete probabilityLicense

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 metadata7.28 Molecular Biology (MIT) 7.28 Molecular Biology (MIT)

Description

This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized. This course covers a detailed analysis of the biochemical mechanisms that control the maintenance, expression, and evolution of prokaryotic and eukaryotic genomes. The topics covered in lectures and readings of relevant literature include gene regulation, DNA replication, genetic recombination, and mRNA translation. In particular, the logic of experimental design and data analysis is emphasized.Subjects

molecular biology | molecular biology | biochemical mechanisms | biochemical mechanisms | gene expression | gene expression | evolution | evolution | prokaryotic genome | prokaryotic genome | eukaryotic genomes | eukaryotic genomes | gene regulation | gene regulation | DNA replication | DNA replication | genetic recombination | genetic recombination | RNA processing | RNA processing | translation | translation | genome | genomeLicense

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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The course is an introduction to the approach of Reflective Practice developed by Donald Schön. It is an approach that enables professionals to understand how they use their knowledge in practical situations and how they can combine practice and learning in a more effective way. Through greater awareness of how they deploy their knowledge in practical situations, professionals can increase their capacities of learning in a more timely way. Understanding how they frame situations and ideas helps professionals to achieve greater flexibility and increase their capacity of conceptual innovation. The objective of the course is to introduce students to the approach and methods of reflective practice by raising their awareness about their own cognitive resources and how they use them in thei The course is an introduction to the approach of Reflective Practice developed by Donald Schön. It is an approach that enables professionals to understand how they use their knowledge in practical situations and how they can combine practice and learning in a more effective way. Through greater awareness of how they deploy their knowledge in practical situations, professionals can increase their capacities of learning in a more timely way. Understanding how they frame situations and ideas helps professionals to achieve greater flexibility and increase their capacity of conceptual innovation. The objective of the course is to introduce students to the approach and methods of reflective practice by raising their awareness about their own cognitive resources and how they use them in theiSubjects

reflective practice | Donald Schon | Chris Argyris | conceptual innovation | knowledge generation | espoused theory | theory in use | reflection | tacit knowledge | explicit knowledge | learning cycles | reframing | conceptual frameworks | critical moments | experimentation | speculation | modeling | dialogue | theories | action | thinking | virtual worlds | mental model | framing | justice | equality | power | assumptions | intractable controversies | reflective practice | Donald Schon | Chris Argyris | conceptual innovation | knowledge generation | espoused theory | theory in use | reflection | tacit knowledge | explicit knowledge | learning cycles | reframing | conceptual frameworks | critical moments | experimentation | speculation | modeling | dialogue | theories | action | thinking | virtual worlds | mental model | framing | justice | equality | power | assumptions | intractable controversies | diagrams | diagrams | reflective practice | reflective practice | Donald Schon | Donald Schon | practice | practice | learning | learning | conceptual innovation | conceptual innovation | cognitive resources | cognitive resources | socialization | socialization | externalization | externalization | combination | combination | internalization | internalization | SECI Cycle of Knowledge | SECI Cycle of KnowledgeLicense

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See all metadata6.004 Computation Structures (MIT) 6.004 Computation Structures (MIT)

Description

6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples. 6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computer 6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples. 6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computerSubjects

computation | computation | computation structure | computation structure | primitives | primitives | gates | gates | instructions | instructions | procedures | procedures | processes | processes | concurrency | concurrency | instruction set design | instruction set design | software structure | software structure | digital system | digital system | MOS transistor | MOS transistor | logic gate | logic gate | combinational circuit | combinational circuit | sequential circuit | sequential circuit | finite-state machines | finite-state machines | computer architecture | computer architecture | programming | programming | RISC processor | RISC processorLicense

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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See all metadata6.004 Computation Structures (MIT) 6.004 Computation Structures (MIT)

Description

6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks - logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples.6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. Before taking 6.004, students should feel comfortable using computers; a rudimentary knowledge of programming language concepts (6.001) and electrical fundamentals (6.002) is assumed. 6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks - logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples.6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. Before taking 6.004, students should feel comfortable using computers; a rudimentary knowledge of programming language concepts (6.001) and electrical fundamentals (6.002) is assumed.Subjects

computation | computation | computation structure | computation structure | primitives | primitives | gates | gates | nstructions | nstructions | procedures | procedures | processes | processes | concurrency | concurrency | instruction set design | instruction set design | software structure | software structure | digital system | digital system | MOS transistor | MOS transistor | logic gate | logic gate | combinational circuit | combinational circuit | sequential circuit | | sequential circuit | | finite-state machines | finite-state machines | sequential circuit | sequential circuit | computer architecture | computer architecture | programming | programming | RISC processor | RISC processor | instructions | instructionsLicense

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 metadata8.902 Astrophysics II (MIT) 8.902 Astrophysics II (MIT)

Description

This is the second course in a two-semester sequence on astrophysics. Topics include galactic dynamics, groups and clusters on galaxies, phenomenological cosmology, Newtonian cosmology, Roberston-Walker models, and galaxy formation. This is the second course in a two-semester sequence on astrophysics. Topics include galactic dynamics, groups and clusters on galaxies, phenomenological cosmology, Newtonian cosmology, Roberston-Walker models, and galaxy formation.Subjects

Galactic dynamics | Galactic dynamics | potential theory | potential theory | orbits | orbits | collisionless Boltzmann equations | collisionless Boltzmann equations | Galaxy interactions | Galaxy interactions | Groups and clusters | Groups and clusters | dark matter | dark matter | Intergalactic medium | Intergalactic medium | x-ray clusters | x-ray clusters | Active galactic nuclei | Active galactic nuclei | unified models | unified models | black hole accretion | black hole accretion | radio and optical jets | radio and optical jets | Homogeneity and isotropy | Homogeneity and isotropy | redshift | redshift | galaxy distance ladder | galaxy distance ladder | Newtonian cosmology | Newtonian cosmology | Roberston-Walker models and cosmography | Roberston-Walker models and cosmography | Early universe | Early universe | primordial nucleosynthesis | primordial nucleosynthesis | recombination | recombination | Cosmic microwave background radiation | Cosmic microwave background radiation | Large-scale structure | Large-scale structure | galaxy formation | galaxy formationLicense

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 metadata12.864 Inference from Data and Models (MIT) 12.864 Inference from Data and Models (MIT)

Description

The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themeslinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc. The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themeslinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc.Subjects

observation | observation | kinematical models | kinematical models | dynamical models | dynamical models | basic statistics | basic statistics | linear algebra | linear algebra | inverse methods | inverse methods | singular value decompositions | singular value decompositions | control theory | control theory | sequential estimation | sequential estimation | Kalman filters | Kalman filters | smoothing algorithms | smoothing algorithms | adjoint/Pontryagin principle methods | adjoint/Pontryagin principle methods | model testing | model testing | stationary processes | stationary processes | Fourier methods | Fourier methods | z-transforms | z-transforms | sampling theorems | sampling theorems | spectra | spectra | multi-taper methods | multi-taper methods | coherences | coherences | filtering | filtering | quantitative combinations | quantitative combinations | realistic observations | realistic observations | data assimilations | data assimilations | deduction | deduction | regression | regression | objective mapping | objective mapping | time series analysis | time series analysis | inference | inferenceLicense

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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See all metadata7.345 The Science of Sperm (MIT) 7.345 The Science of Sperm (MIT)

Description

Sperm are tiny, haploid cells with a supremely important job: They deliver the paternal genome to the egg, helping create a zygote that develops into a new individual. For a human male, however, only a small fraction of the sperm produced will ever fertilize an egg. Sperm thus experience intense selective pressure: They must compete against each other, navigate a foreign environment in the female reproductive tract, and interact specifically and appropriately with the surface of the egg. These selective pressures can drive extreme changes in morphology and gene function over short evolutionary time scales, resulting in amazing diversity among species. In this course, we will explore the ways in which these unique evolutionary forces contribute to incredible specializations of sperm form an Sperm are tiny, haploid cells with a supremely important job: They deliver the paternal genome to the egg, helping create a zygote that develops into a new individual. For a human male, however, only a small fraction of the sperm produced will ever fertilize an egg. Sperm thus experience intense selective pressure: They must compete against each other, navigate a foreign environment in the female reproductive tract, and interact specifically and appropriately with the surface of the egg. These selective pressures can drive extreme changes in morphology and gene function over short evolutionary time scales, resulting in amazing diversity among species. In this course, we will explore the ways in which these unique evolutionary forces contribute to incredible specializations of sperm form anSubjects

sperm | sperm | sperm biology | sperm biology | haploid cells | haploid cells | sperm development | sperm development | selective forces | selective forces | meiotic cell division | meiotic cell division | protamines | protamines | fertilization | fertilization | evolutionary analysis | evolutionary analysis | reproductive biology | reproductive biology | spermatogenesis | spermatogenesis | spermatogenic cycle | spermatogenic cycle | germline mutations | germline mutations | FGFR2 gene | FGFR2 gene | germ line selection | germ line selection | Fragile X syndrome | Fragile X syndrome | Meiotic recombination | Meiotic recombination | sperm bundling | sperm bundling | Sperm Cooperation | Sperm Cooperation | sperm competition | sperm competitionLicense

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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See all metadata12.864 Inference from Data and Models (MIT) 12.864 Inference from Data and Models (MIT)

Description

This course covers the fundamental methods used for exploring the information content of observations related to kinematical and dynamical models. This course covers the fundamental methods used for exploring the information content of observations related to kinematical and dynamical models.Subjects

kinematical and dynamical models | kinematical and dynamical models | Basic statistics | Basic statistics | linear algebra | linear algebra | inverse methods | inverse methods | singular value decompositions | singular value decompositions | control theory | control theory | sequential estimation | sequential estimation | Kalman filters | Kalman filters | smoothing algorithms | smoothing algorithms | adjoint/Pontryagin principle methods | adjoint/Pontryagin principle methods | model testing | model testing | stationary processes | stationary processes | Fourier methods | Fourier methods | z-transforms | z-transforms | sampling theorems | sampling theorems | spectra | spectra | multi-taper methods | multi-taper methods | coherences | coherences | filtering | filtering | quantitative combinations of models | quantitative combinations of modelsLicense

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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See all metadataTALAT Lecture 2204: Design Philosophy TALAT Lecture 2204: Design Philosophy

Description

This lecture outlines the requirements on load bearing structures with respect to safety against failure; it introduces the design analysis process with methods of verification and partial safety factors; it describes the characteristic of loads and load combinations on structures; it introduces the subject of load and resistance factors in the verification methods; it describes the basic structural design properties of aluminium alloys versus steel. Some background and experience in structural engineering and design calculations; basic understanding of the physical and mechanical properties of aluminium is assumed. This lecture outlines the requirements on load bearing structures with respect to safety against failure; it introduces the design analysis process with methods of verification and partial safety factors; it describes the characteristic of loads and load combinations on structures; it introduces the subject of load and resistance factors in the verification methods; it describes the basic structural design properties of aluminium alloys versus steel. Some background and experience in structural engineering and design calculations; basic understanding of the physical and mechanical properties of aluminium is assumed.Subjects

aluminium | aluminium | aluminum | aluminum | european aluminium association | european aluminium association | EAA | EAA | Training in Aluminium Application Technologies | Training in Aluminium Application Technologies | training | training | metallurgy | metallurgy | technology | technology | lecture | lecture | design | design | product | product | structural design | structural design | load carrying structure | load carrying structure | safety | safety | serviceability | serviceability | limit states | limit states | economic considerations | economic considerations | verification | verification | load and resistance design factor method | load and resistance design factor method | method of allowable stresses | method of allowable stresses | characteristic loads | characteristic loads | normal loads | normal loads | long-term loads | long-term loads | load combinations | load combinations | design value of the load | design value of the load | buildings | buildings | bridges | bridges | hydraulic structures | hydraulic structures | resistance | resistance | strength properties | strength properties | corematerials | corematerials | ukoer | ukoerLicense

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6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models and parasitics; device sizing and logical effort; timing issues (clock skew and jitter) and active clock distribution techniques; memory architectures, circuits (sense amplifiers) and devices; testing of integrated circuits. The course employs extensive use of circuit layout and SPICE in design projects and software labs. 6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models and parasitics; device sizing and logical effort; timing issues (clock skew and jitter) and active clock distribution techniques; memory architectures, circuits (sense amplifiers) and devices; testing of integrated circuits. The course employs extensive use of circuit layout and SPICE in design projects and software labs.Subjects

digital integrated circuit | device | circuit | digital | MOS | digital integrated circuit | device | circuit | digital | MOS | digital integrated circuit | digital integrated circuit | device | device | circuit | circuit | digital | digital | MOS | MOS | Deep Sub-Micron effects | Deep Sub-Micron effects | circuit design | circuit design | logic | logic | interconnect models; parasitics | interconnect models; parasitics | device sizing | device sizing | timing | timing | clock skew | clock skew | jitter; clock distribution techniques | jitter; clock distribution techniques | memory architectures | memory architectures | circuits | circuits | sense amplifiers | sense amplifiers | SPICE | SPICE | HSPICE | HSPICE | Magic | Magic | Nanosim | Nanosim | Avanwaves | Avanwaves | device level optimization | device level optimization | interconnect models | interconnect models | parasitics | parasitics | jitter | jitter | clock distribution techniques | clock distribution techniques | CMOS inverter | CMOS inverter | combinational logic | combinational logic | sequential circuits | sequential circuitsLicense

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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See all metadata6.004 Computation Structures (MIT) 6.004 Computation Structures (MIT)

Description

6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples. 6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computer 6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples. 6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computerSubjects

computation | computation | computation structure | computation structure | primitives | primitives | gates | gates | instructions | instructions | procedures | procedures | processes | processes | concurrency | concurrency | instruction set design | instruction set design | software structure | software structure | digital system | digital system | MOS transistor | MOS transistor | logic gate | logic gate | combinational circuit | combinational circuit | sequential circuit | sequential circuit | finite-state machines | finite-state machines | computer architecture | computer architecture | programming | programming | RISC processor | RISC processorLicense

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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Directed evolution has been used to produce enzymes with many unique properties. The technique of directed evolution comprises two essential steps: mutagenesis of the gene encoding the enzyme to produce a library of variants, and selection of a particular variant based on its desirable catalytic properties. In this course we will examine what kinds of enzymes are worth evolving and the strategies used for library generation and enzyme selection. We will focus on those enzymes that are used in the synthesis of drugs and in biotechnological applications. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current Directed evolution has been used to produce enzymes with many unique properties. The technique of directed evolution comprises two essential steps: mutagenesis of the gene encoding the enzyme to produce a library of variants, and selection of a particular variant based on its desirable catalytic properties. In this course we will examine what kinds of enzymes are worth evolving and the strategies used for library generation and enzyme selection. We will focus on those enzymes that are used in the synthesis of drugs and in biotechnological applications. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about currentSubjects

evolution | evolution | biocatalyst | biocatalyst | mutation | mutation | library | library | recombination | recombination | directed evolution | directed evolution | enzyme | enzyme | point mutation | point mutation | mutagenesis | mutagenesis | DNA | DNA | gene | gene | complementation | complementation | affinity | affinity | phage | phage | ribosome display | ribosome display | yeast surface display | yeast surface display | bacterial cell surface display | bacterial cell surface display | IVC | IVC | FACS | FACS | active site | active siteLicense

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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See all metadata7.03 Genetics (MIT) 7.03 Genetics (MIT)

Description

The principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. Structure and function of genes, chromosomes and genomes. Biological variation resulting from recombination, mutation, and selection. Population genetics. Use of genetic methods to analyze protein function, gene regulation and inherited disease. The principles of genetics with application to the study of biological function at the level of molecules, cells, and multicellular organisms, including humans. Structure and function of genes, chromosomes and genomes. Biological variation resulting from recombination, mutation, and selection. Population genetics. Use of genetic methods to analyze protein function, gene regulation and inherited disease.Subjects

Population genetics | Population genetics | selection | selection | mutation | mutation | recombination | recombination | genomes | genomes | chromosomes | chromosomes | genes | genesLicense

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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