# An Introduction to Probability in Computing

- Institution: IIT Madras
- Department: Computer Science and Engineering
- Teacher: Prof. John Augustine
- Level: Undergraduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106106176)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106106176)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

## Lectures

1. [Introduction to Probability - A box of chocolates](https://invisiblenetwork.ai/learn/nptel/106106176/b597803ce4f6) (Video)
2. [Introduction to Probability - Axiomatic Approach to Probability Theory](https://invisiblenetwork.ai/learn/nptel/106106176/d509de1c714e) (Video)
3. [Introduction to Probability - Verifying Matrix Multipilication ( Statement,Algorithm & Independence )](https://invisiblenetwork.ai/learn/nptel/106106176/0020fa4de200) (Video)
4. [Introduction to Probability - Verifying Matrix Multipilication ( Correctness & Law of Total Probability )](https://invisiblenetwork.ai/learn/nptel/106106176/7bfcd813dfea) (Video)
5. [Introduction to Probability - How Strong is your Network?](https://invisiblenetwork.ai/learn/nptel/106106176/e7b342f8b0c6) (Video)
6. [Introduction to Probability - How to Understand the World? Play with it!](https://invisiblenetwork.ai/learn/nptel/106106176/63f4db5e8af3) (Video)
7. [Tutorial 1](https://invisiblenetwork.ai/learn/nptel/106106176/e7a8f277f0b8) (Video)
8. [Tutorial 2](https://invisiblenetwork.ai/learn/nptel/106106176/73aedd37c237) (Video)
9. [Discrete Random Variables - Basic Definitions](https://invisiblenetwork.ai/learn/nptel/106106176/a8abef3e91c7) (Video)
10. [Discrete Random Variables - Linearity of Expectation & Jensens Inequality](https://invisiblenetwork.ai/learn/nptel/106106176/af891ecd111f) (Video)
11. [Discrete Random Variables - Conditional Expectation I](https://invisiblenetwork.ai/learn/nptel/106106176/9af2499b5d59) (Video)
12. [Discrete Random Variables - Conditional Expectation II](https://invisiblenetwork.ai/learn/nptel/106106176/ca511a0f5725) (Video)
13. [Discrete Random Variables - Geometric Random Variables & Collecting Coupons](https://invisiblenetwork.ai/learn/nptel/106106176/ac9583dcac08) (Video)
14. [Discrete Random Variables - Randomized Selection](https://invisiblenetwork.ai/learn/nptel/106106176/75a456540cfb) (Video)
15. [Tail Bounds I - Markov's Inequality](https://invisiblenetwork.ai/learn/nptel/106106176/e3f6909bf0df) (Video)
16. [Tail Bounds I - The Second Moment,Variance & Chebyshev's Inequality](https://invisiblenetwork.ai/learn/nptel/106106176/d5743102f67b) (Video)
17. [Tail Bounds I - Median via Sampling](https://invisiblenetwork.ai/learn/nptel/106106176/15157f3bbc8e) (Video)
18. [Tail Bounds I - Median via Sampling - Analysis](https://invisiblenetwork.ai/learn/nptel/106106176/ec2bef6295fb) (Video)
19. [Tail Bounds I - Moment Generating Functions and Chernoff Bounds](https://invisiblenetwork.ai/learn/nptel/106106176/71522d0611f1) (Video)
20. [Tail Bounds I - Parameter Estimation](https://invisiblenetwork.ai/learn/nptel/106106176/bf80432c196a) (Video)
21. [Tail Bounds I - Control Group Selection](https://invisiblenetwork.ai/learn/nptel/106106176/5259e57a4a8c) (Video)
22. [Applications of Tail Bounds - Routing in Sparse Networks](https://invisiblenetwork.ai/learn/nptel/106106176/c102a9303819) (Video)
23. [Applications of Tail Bounds - Analysis of Valiant's Rounting](https://invisiblenetwork.ai/learn/nptel/106106176/ea44ebc7863a) (Video)
24. [Applications of Tail Bounds - Random Graphs](https://invisiblenetwork.ai/learn/nptel/106106176/a038cc798438) (Video)