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    Quick Facts

    Medium Of InstructionsMode Of LearningMode Of Delivery
    EnglishSelf StudyVideo and Text Based

    Courses and Certificate Fees

    Certificate AvailabilityCertificate Providing Authority
    yesIIT Kanpur

    The Syllabus

    • Linear Programming, an Example
    • Introduction to Linear Programming
    • Gaussian Elimination with Examples
    • Summary of Gaussian Elimination

    • Vector Space over real numbers
    • Linear Operators
    • Solutions of Linear Equations
    • Resource Allocation as LP
    • Approximate Degree as LP
    • Equivalent LP's

    • Introduction to Convexity
    • Different Kind of Convex Sets
    • Feasible Region of LP
    • Proof of Weyl's Theorem
    • Definition of Convex Functions
    • Properties of Convex Functions and Examples

    • Basic Feasible Solution
    • BFS and Vertices
    • Simplex Algorithm
    • Details of Simplex Algorithm
    • Starting BFS
    • Degeneracy
    • Introduction to Duality

    • Hyperplane Separation Theorems
    • Farkas Lemma
    • How to take dual
    • Examples of taking dual
    • Strong Duality
    • Proof of Strong Duality
    • Complementary Slackness

    • Introduction to Algorithmic Game Theory
    • Nash Equilibrium
    • Minimax and Nash Equilibrium
    • Deterministic Communication Complexity
    • Randomized Communication Complexity
    • Yao's Minimax Theorem
    • Lower bounds using Yao's Minimax

    • Set Disjointness Problem
    • LP for mass flow problem
    • LP for min cut problem
    • Max flow = Min cut
    • Primal dual approach
    • Primal dual for max flow

    • Set cover problem
    • Rounding for set cover
    • Analysis of Rounding
    • Algorithm for Set Cover
    • Linear Regression through LP
    • Linear Classifiers through LP

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