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Last updated:

September 25, 2023

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

Probability for Computer Science. Instructor: Prof. Nitin Saxena, Department of Computer Science and Engineering, IIT Kanpur.

Probability is one of the most important ideas in human knowledge. This is a crash course to introduce the concept of probability formally; and exhibit its applications in computer science, combinatorics, and algorithms. The course will be different from a typical mathematics course in the coverage and focus of examples. After finishing this course a student will have a good understanding of both theory and practice of probability in diverse areas. (from nptel.ac.in)

Course Curriculum

  • Lecture 01 – Introductory Examples Unlimited
  • Lecture 02 – Examples and Course Outline Unlimited
  • Lecture 03 – Probability over Discrete Space Unlimited
  • Lecture 04 – Inclusion-Exclusion Principle Unlimited
  • Lecture 05 – Probability over Infinite Space Unlimited
  • Lecture 06 – Conditional Probability, Partition Formula Unlimited
  • Lecture 07 – Independent Events, Bayes Theorem Unlimited
  • Lecture 08 – Fallacies, Random Variables Unlimited
  • Lecture 09 – Expectation Unlimited
  • Lecture 10 – Conditional Expectation Unlimited
  • Lecture 11 – Important Random Variables Unlimited
  • Lecture 12 – Continuous Random Variables Unlimited
  • Lecture 13 – Equality Checking, Poisson Distribution Unlimited
  • Lecture 14 – Concentration Inequalities, Variance Unlimited
  • Lecture 15 – Weak Linearity of Variance, Law of Large Numbers Unlimited
  • Lecture 16 – Chernoff’s Bound, K-wise Independence Unlimited
  • Lecture 17 – Union and Factorial Estimates Unlimited
  • Lecture 18 – Stochastic Process: Markov Chains Unlimited
  • Lecture 19 – Drunkard’s Walk, Evolution of Markov Chains Unlimited
  • Lecture 20 – Stationary Distribution Unlimited
  • Lecture 21 – Ferron-Frobenius Theorem, PageRank Algorithm Unlimited
  • Lecture 22 – PageRank Algorithm: Ergodicity Unlimited
  • Lecture 23 – Cell Genetics Unlimited
  • Lecture 24 – Random Sampling Unlimited
  • Lecture 25 – Biased Coin Tosses, Hashing Unlimited
  • Lecture 26 – Hashing, Introduction to Probabilistic Methods Unlimited
  • Lecture 27 – Ramsey Numbers, Large Cuts in Graphs Unlimited
  • Lecture 28 – Sum Free Subsets, Discrepancy Unlimited
  • Lecture 29 – Extremal Set Families Unlimited
  • Lecture 30 – Super Concentrators Unlimited
  • Lecture 31 – Streaming Algorithms I Unlimited
  • Lecture 32 – Streaming Algorithms II Unlimited

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