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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 - Induction and recursion

Description

This class test forms part of the "Induction and Recursion" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts test | induction and recursion | induction | recursion | computer science | computer science concept | computer science concepts | induction and recursion class test | induction class test | recursion class test | computer science class test | computer science concept class test | computer science concepts class test | Computer science | I100License

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See all metadataComputer Science Concepts - Induction and recursion

Description

This class test forms part of the "Induction and Recursion" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts test | induction and recursion | induction | recursion | computer science | computer science concept | computer science concepts | induction and recursion class test | induction class test | recursion class test | computer science class test | computer science concept class test | computer science concepts class test | Computer science | I100License

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See all metadataComputer Science Concepts - Induction and recursion

Description

This assignment forms part of the "Induction and Recursion" topic of the Computer Science Concepts module.Subjects

ukoer | computer science concepts assignment | induction and recursion | induction | recursion | computer science | computer science concept | computer science concepts | induction and recursion assignment | induction assignment | recursion assignment | computer science assignment | computer science concept assignment | Computer science | I100License

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See all metadataComputer Science Concepts - Induction and recursion

Description

This lecture forms part of the "Induction and Recursion" topic of the Computer Science Concepts module.Subjects

ukoer | induction and recursion lecture | induction lecture | recursion lecture | induction and recursion | induction | computer science | computer science concept | computer science concepts | computer science lecture | computer science concept lecture | computer science concepts lecture | Computer science | I100License

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This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic. This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic.Subjects

discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math | discrete math | discrete mathematics | discrete mathematics | discrete | discrete | math | math | mathematics | mathematics | seminar | seminar | presentations | presentations | student presentations | student presentations | oral | oral | communication | communication | stable marriage | stable marriage | dych | dych | emergency | emergency | response vehicles | response vehicles | ambulance | ambulance | game theory | game theory | congruences | congruences | color theorem | color theorem | four color | four color | cake cutting | cake cutting | algorithm | algorithm | RSA | RSA | encryption | encryption | numberical integration | numberical integration | sorting | sorting | post correspondence problem | post correspondence problem | PCP | PCP | ramsey | ramsey | van der waals | van der waals | fibonacci | fibonacci | recursion | recursion | domino | domino | tiling | tiling | towers | towers | hanoi | hanoi | pigeonhole | pigeonhole | principle | principle | matrix | matrix | hamming | hamming | code | code | hat game | hat game | juggling | juggling | zero-knowledge | zero-knowledge | proof | proof | repeated games | repeated games | lewis carroll | lewis carroll | determinants | determinants | infinitude of primes | infinitude of primes | bridges | bridges | konigsberg | konigsberg | koenigsberg | koenigsberg | time series analysis | time series analysis | GARCH | GARCH | rational | rational | recurrence | recurrence | relations | relations | digital | digital | image | image | compression | compression | quantum computing | quantum computingLicense

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 is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic. This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic.Subjects

discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math | discrete math | discrete mathematics | discrete mathematics | discrete | discrete | math | math | mathematics | mathematics | seminar | seminar | presentations | presentations | student presentations | student presentations | oral | oral | communication | communication | stable marriage | stable marriage | dych | dych | emergency | emergency | response vehicles | response vehicles | ambulance | ambulance | game theory | game theory | congruences | congruences | color theorem | color theorem | four color | four color | cake cutting | cake cutting | algorithm | algorithm | RSA | RSA | encryption | encryption | numberical integration | numberical integration | sorting | sorting | post correspondence problem | post correspondence problem | PCP | PCP | ramsey | ramsey | van der waals | van der waals | fibonacci | fibonacci | recursion | recursion | domino | domino | tiling | tiling | towers | towers | hanoi | hanoi | pigeonhole | pigeonhole | principle | principle | matrix | matrix | hamming | hamming | code | code | hat game | hat game | juggling | juggling | zero-knowledge | zero-knowledge | proof | proof | repeated games | repeated games | lewis carroll | lewis carroll | determinants | determinants | infinitude of primes | infinitude of primes | bridges | bridges | konigsberg | konigsberg | koenigsberg | koenigsberg | time series analysis | time series analysis | GARCH | GARCH | rational | rational | recurrence | recurrence | relations | relations | digital | digital | image | image | compression | compression | quantum computing | quantum computingLicense

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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Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language. Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.Subjects

computer science | computer science | computation | computation | problem solving | problem solving | Python programming | Python programming | recursion | recursion | binary search | binary search | classes | classes | inheritance | inheritance | libraries | libraries | algorithms | algorithms | optimization problems | optimization problems | modules | modules | simulation | simulation | big O notation | big O notation | control flow | control flow | exceptions | exceptions | building computational models | building computational models | software engineering | software engineeringLicense

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 introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate computational solutions to abstract problems. Substantial weekly programming assignments are an integral part of the course. This course is worth 4 Engineering Design Points.Technical RequirementsScheme software is required to run the .scm files found on this course site. This course introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate computational solutions to abstract problems. Substantial weekly programming assignments are an integral part of the course. This course is worth 4 Engineering Design Points.Technical RequirementsScheme software is required to run the .scm files found on this course site.Subjects

programming | programming | Scheme | Scheme | abstraction | abstraction | recursion | recursion | iteration | iteration | object oriented | object oriented | structure | structure | interpretation | interpretation | computer programs | computer programs | languages | languages | procedures | proceduresLicense

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 metadata18.304 Undergraduate Seminar in Discrete Mathematics (MIT)

Description

This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic.Subjects

discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math | discrete mathematics | discrete | math | mathematics | seminar | presentations | student presentations | oral | communication | stable marriage | dych | emergency | response vehicles | ambulance | game theory | congruences | color theorem | four color | cake cutting | algorithm | RSA | encryption | numberical integration | sorting | post correspondence problem | PCP | ramsey | van der waals | fibonacci | recursion | domino | tiling | towers | hanoi | pigeonhole | principle | matrix | hamming | code | hat game | juggling | zero-knowledge | proof | repeated games | lewis carroll | determinants | infinitude of primes | bridges | konigsberg | koenigsberg | time series analysis | GARCH | rational | recurrence | relations | digital | image | compression | quantum computingLicense

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 will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.Subjects

Python | Python | conditionals | conditionals | loops | loops | defining functions | defining functions | strings | strings | lists | lists | list comprehensions | list comprehensions | recursion | recursion | tuples | tuples | dictionaries | dictionaries | classes | classes | inheritance | inheritance | scoping | scopingLicense

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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Topics covered: Decomposition and abstraction through functions; introduction to recursion Instructor: Prof. Eric Grimson, Prof. John GuttagTranscript: PDFSubtitles: SRTThumbnail - JPG (OCW)Video - download: Internet Archive (MP4)Video - download: iTunes U (MP4)Video - stream: VideoLectures.net Video - stream: YouTube (CC BY-NC-SA) Topics covered: Decomposition and abstraction through functions; introduction to recursion Instructor: Prof. Eric Grimson, Prof. John GuttagTranscript: PDFSubtitles: SRTThumbnail - JPG (OCW)Video - download: Internet Archive (MP4)Video - download: iTunes U (MP4)Video - stream: VideoLectures.net Video - stream: YouTube (CC BY-NC-SA)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.htmDescription

Includes audio/video content: AV lectures. This course introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate computational solutions to abstract problems. Substantial weekly programming assignments are an integral part of the course. This course is worth 4 Engineering Design Points. Includes audio/video content: AV lectures. This course introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate computational solutions to abstract problems. Substantial weekly programming assignments are an integral part of the course. This course is worth 4 Engineering Design Points.Subjects

programming | programming | Scheme | Scheme | abstraction | abstraction | recursion | recursion | iteration | iteration | object oriented | object oriented | structure | structure | interpretation | interpretation | computer programs | computer programs | languages | languages | procedures | proceduresLicense

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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This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.Subjects

computer science | computer science | computation | computation | problem solving | problem solving | Python programming | Python programming | recursion | recursion | binary search | binary search | classes | classes | inheritance | inheritance | libraries | libraries | algorithms | algorithms | optimization problems | optimization problems | modules | modules | simulation | simulation | big O notation | big O notation | control flow | control flow | exceptions | exceptions | building computational models | building computational models | software engineering | software engineeringLicense

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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6.01 explores fundamental ideas in electrical engineering and computer science, in the context of working with mobile robots. Key engineering principles, such as abstraction and modularity, are applied in the design of computer programs, electronic circuits, discrete-time controllers, and noisy and/or uncertain systems. 6.01 explores fundamental ideas in electrical engineering and computer science, in the context of working with mobile robots. Key engineering principles, such as abstraction and modularity, are applied in the design of computer programs, electronic circuits, discrete-time controllers, and noisy and/or uncertain systems.Subjects

robots | robots | python | python | computer programs | computer programs | circuits | circuits | systems | systems | inheritance | inheritance | recursion | recursion | functional programming | functional programming | signals | signals | control | control | circuit abstractions | circuit abstractions | probability | probability | discrete probability | discrete probability | search algorithms | search algorithms | state machines | state machines | probabilistic state estimation | probabilistic state estimation | decision-making | decision-making | search | search | python robots | python robotsLicense

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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Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language. Includes audio/video content: AV lectures. This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.Subjects

Python programming | Python programming | algorithms | algorithms | dynamic programming | dynamic programming | object-oriented programming | object-oriented programming | debugging | debugging | problem solving | problem solving | recursion | recursion | iteration | iteration | search algorithms | search algorithms | program efficiency | program efficiency | order of growth | order of growth | memoization | memoization | hashing | hashing | object classes | object classes | inheritance | inheritance | Monte Carlo simulation | Monte Carlo simulation | curve fitting | curve fitting | optimization | optimization | clustering | clustering | queuing networks | queuing networks | data sampling | data samplingLicense

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 describes discrete mathematics, which involves processes that consist of sequences of individual steps (as compared to calculus, which describes processes that change in a continuous manner). The principal topics presented in this course are logic and proof, induction and recursion, discrete probability, and finite state machines. This free course may be completed online at any time. See course site for detailed overview and learning outcomes. (Computer Science 202)Subjects

discrete structures | truth tables | negations | tautologies | conditional statements | modus ponens | modus tollens | generalization | specialization | elimination | quantified | quantifiers | number theory | divisibility | induction | sequences | notation | set theory | recursion | automata | Computer science | I100License

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See all metadata6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

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 | introduction to programming | how to think like a computer scientist | control flow | lists | strings | tuples | objects | mutability | scope | dictionaries | web search | recursion | branching and repetition | structuring programs | debugging programs | data structures | teamwork | modularity | 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 metadata6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

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 | introduction to programming | how to think like a computer scientist | control flow | lists | strings | tuples | objects | mutability | scope | dictionaries | web search | recursion | branching and repetition | structuring programs | debugging programs | data structures | teamwork | modularity | 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 metadata4: Abstraction through Functions; Introduction to Recursion

Description

Topics covered: Decomposition and abstraction through functions; introduction to recursion Instructor: Prof. Eric Grimson, Prof. John GuttagTranscript: PDFSubtitles: SRTThumbnail - JPG (OCW)Video - download: Internet Archive (MP4)Video - download: iTunes U (MP4)Video - stream: VideoLectures.net Video - stream: YouTube (CC BY-NC-SA)License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

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

http://ocw.mit.edu/rss/all/mit-allthaicourses.xmlAttribution

Click to get HTML | Click to get attribution | Click to get URLAll metadata

See all metadata6.189 A Gentle Introduction to Programming Using Python (MIT)

Description

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 | introduction to programming | how to think like a computer scientist | control flow | lists | strings | tuples | objects | mutability | scope | dictionaries | web search | recursion | branching and repetition | structuring programs | debugging programs | data structures | teamwork | modularity | 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 metadata6.00 Introduction to Computer Science and Programming (MIT)

Description

This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python™ programming language.Subjects

computer science | computation | problem solving | Python programming | recursion | binary search | classes | inheritance | libraries | algorithms | optimization problems | modules | simulation | big O notation | control flow | exceptions | building computational models | software engineeringLicense

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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