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This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms,...
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This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
Material Type:
Online Course
Author:
Prof. Erik Demaine Prof. Ronald Rivest Prof. Srinivas Devadas
Date Added:
Aug 10, 2012
Date Modified:
Aug 10, 2012
Peer Review for material titled "6.006 Introduction to Algorithms"
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This course is offered both to undergraduates (6.041) and graduates (6.431), but the assignments differ. 6.041/6.431...
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This course is offered both to undergraduates (6.041) and graduates (6.431), but the assignments differ. 6.041/6.431 introduces students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, transform techniques, simple random processes and their probability distributions, Markov processes, limit theorems, and elements of statistical inference.
This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides...
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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 aÂ previous termÂ was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science).
Material Type:
Online Course
Author:
Prof. Ronitt Rubinfeld Prof. Albert Meyer
Date Added:
Aug 10, 2012
Date Modified:
Aug 10, 2012
Peer Review for material titled "6.042J / 18.062J Mathematics for Computer Science"
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This course is offered to undergraduates and is an elementary discrete mathematics course oriented towards applications in...
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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.
Material Type:
Online Course
Author:
Prof. Charles Leiserson(Contributor) Dr. Eric Lehman Prof. Srinivas Devadas Prof. Albert Meyer(Contributor)
Date Added:
Aug 10, 2012
Date Modified:
Aug 10, 2012
Peer Review for material titled "6.042J / 18.062J Mathematics for Computer Science"
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This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides...
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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. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science). Contributors Srinivas Devadas Lars Engebretsen David Karger Eric Lehman Thomson Leighton Charles Leiserson Nancy Lynch Santosh Vempala
Material Type:
Online Course
Author:
Dr. Radhika Nagpal Prof. Albert Meyer
Date Added:
Aug 10, 2012
Date Modified:
Oct 03, 2012
Peer Review for material titled "6.042J Mathematics for Computer Science (SMA 5512)"
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This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice....
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This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5503 (Analysis and Design of Algorithms).
Material Type:
Online Course
Author:
Prof. Charles Leiserson Prof. Erik Demaine
Date Added:
Aug 10, 2012
Date Modified:
Aug 10, 2012
Peer Review for material titled "6.046J / 18.410J Introduction to Algorithms (SMA 5503)"
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This course teaches simple reasoning techniques for complex phenomena: divide and conquer, dimensional analysis, extreme...
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This course teaches simple reasoning techniques for complex phenomena: divide and conquer, dimensional analysis, extreme cases, continuity, scaling, successive approximation, balancing, cheap calculus, and symmetry. Applications are drawn from the physical and biological sciences, mathematics, and engineering. Examples include bird and machine flight, neuron biophysics, weather, prime numbers, and animal locomotion. Emphasis is on low-cost experiments to test ideas and on fostering curiosity about phenomena in the world.
Material Type:
Online Course
Author:
Dr. Sanjoy Mahajan
Date Added:
Aug 10, 2012
Date Modified:
Aug 10, 2012
Peer Review for material titled "6.055J / 2.038J The Art of Approximation in Science and Engineering"
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This course is designed for undergraduate and graduate students in science, social science and engineering programs who need...
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This course is designed for undergraduate and graduate students in science, social science and engineering programs who need to learn fundamental programming skills quickly but not in great depth. The course is ideal for undergraduate research positions or summer jobs requiring C++. It is not a class for experienced programmers in C++. Students with no programming background are welcome. Topics include control structures, arrays, functions, classes, objects, file handling, and simple algorithms for common tasks. 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.
Material Type:
Online Course
Author:
Jesse Dunietz Radhika Malik Tanmay Kumar
Date Added:
Aug 10, 2012
Date Modified:
Oct 03, 2012
Peer Review for material titled "6.096 Introduction to C++"
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This course offers an introduction to optimization problems, algorithms, and their complexity, emphasizing basic...
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This course offers an introduction to optimization problems, algorithms, and their complexity, emphasizing basic methodologies and the underlying mathematical structures. The main topics covered include: Theory and algorithms for linear programming Network flow problems and algorithms Introduction to integer programming and combinatorial problems
Material Type:
Online Course
Author:
Prof. John Tsitsiklis
Date Added:
Aug 10, 2012
Date Modified:
Oct 03, 2012
Peer Review for material titled "6.251J / 15.081J Introduction to Mathematical Programming"
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This course relies on primary readings from the database community to introduce graduate students to the foundations of...
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This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken MIT course 6.033 (or equivalent); no prior database experience is assumed though students who have taken an undergraduate course in databases are encouraged to attend. Topics related to the engineering and design of database systems, including: data models; database and schema design; schema normalization and integrity constraints; query processing; query optimization and cost estimation; transactions; recovery; concurrency control; isolation and consistency; distributed, parallel, and heterogeneous databases; adaptive databases; trigger systems; pub-sub systems; semi structured data and XML querying.
Material Type:
Online Course
Author:
Prof. Samuel Madden
Date Added:
Aug 10, 2012
Date Modified:
Oct 03, 2012
Peer Review for material titled "6.830 Database Systems"
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