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Created by:
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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