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The course will present a thorough introduction to the fundamental algorithmic techniques of Discrete Mathematics – Linear and Convex Programming, flow & matching theory, randomization, and approximation. And will cover a variety of optimization problems by applying these techniques to find efficient algorithms and will discuss how fast a maximum matching can be found in a graph and what duality is and how to make use of it.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: MIT

Course Curriculum

Matching Algorithms 00:15:00
Polyhedral Combinatorics 00:10:00
The Matching Polytope Bipartite Graphs 00:05:00
The Matching Polytope General Graphs 00:05:00
Flow Duality and Algorithms 00:10:00
Minimum Cuts 00:05:00
Linear Programs 00:05:00
The Simplex Algorithm 00:15:00
The Primal-dual Algorithm 00:05:00
The Ellipsoid Algorithm 00:05:00
Separation Oracles 00:05:00
NP-completeness 00:10:00
Approximation Algorithms 00:10:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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