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Quick Facts

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

Courses and Certificate Fees

Fees InformationsCertificate AvailabilityCertificate Providing Authority
INR 1000yesIIT Bombay

The Syllabus

  • Introduction to Bandit Algorithms. From Batch to Online Setting

  • Adversarial Setting with Full information (Halving, WM Algorithm )

  • Adversarial Setting with Bandit Information

  • Regret lower bounds for adversarial Setting

  • Introduction to Stochastic Setting and various regret notions

  • A primer on Concentration inequalities

  • Stochastic Bandit Algorithms UCB, KL-UCB

  • Lower bounds for stochastic Bandits

  • Introductions to contextual bandits

  • Overview of contextual bandit algorithms

  • Introduction to pure exploration setups (fixed confidence vs budget)

  • Algorithms for pure explorations (LUCB, KL-LUCB, lil’UCB)

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