Modules / Lectures

Video Transcript:

Auto Scroll Hide


New Assignments
Module NameDownload
Week1Week1
Week1_solutionsWeek1_solutions
Week2Week2
Week2_solutionsWeek2_solutions
Week3Week3
Week3_solutionsWeek3_solutions
Week4Week4
Week4_solutionsWeek4_solutions
Week5Week5
Week5_solutionsWeek5_solutions
Week6Week6
Week6_solutionsWeek6_solutions
Week7Week7
Week7_solutionsWeek7_solutions
Week8Week8
Week8_solutionsWeek8_solutions


Sl.No Chapter Name MP4 Download
1Lesson 1 - Basic definitionsDownload
2Lesson 2 - Conditional probabilityDownload
3Lesson 3 - Example problemsDownload
4Lesson 4 - Karger's mincut algorithmDownload
5Lesson 5 - Analysis of Karger's mincut algorithmDownload
6Lesson 6 - Random variablesDownload
7Lesson 7 - Randomized quicksortDownload
8Problem solving video - The rich get richerDownload
9Problem solving video - Monty Hall problemDownload
10Lesson 1 - Bernoulli, Binomial, and Geometric distributionsDownload
11Lesson 2 - Tail BoundsDownload
12Lesson 3 - Application of Chernoff boundDownload
13Lesson 4 - Application of Chebyshev's inequalityDownload
14Lesson 1 - Intro to Big Data AlgorithmsDownload
15Lesson 2 - SAT ProblemDownload
16Lesson 3 - Classification of StatesDownload
17Lesson 4 - Stationary Distribution of a Markov ChainDownload
18Lesson 5 - Celebrities Case StudyDownload
19Lesson 6 - Random Walks on Undirected GraphsDownload
20Lesson 7 - Intro to Streaming, Morris AlgorithmDownload
21Lesson 8 - Reservoir SamplingDownload
22Lesson 9 - Approximate MedianDownload
23Lesson 1 : OverviewDownload
24Lesson 2 : Balls, bins, hashingDownload
25Lesson 3 : Chain hashing, SUHA, Power of Two choicesDownload
26Lesson 4 : Bloom filterDownload
27Lesson 5 : Pairwise independenceDownload
28Lesson 6 : Estimating expectation of continuous functionDownload
29Lesson 1 - Universal hash functionsDownload
30Lesson 2 - Perfect hashingDownload
31Lesson 3 - Count-min filter for heavy hitters in data streamsDownload
32Problem solving video - Doubly Stochastic Transition MatrixDownload
33Problem solving video - Random Walks on Linear StructuresDownload
34Problem solving video - Lollipop GraphDownload
35Problem solving video - Cat And MouseDownload
36Lesson 1 - Estimating frequency momentsDownload
37Lesson 2 - Property testing frameworkDownload
38Lesson 3 - Testing ConnectivityDownload
39Lesson 4 - Enforce & Test IntroductionDownload
40Lesson 5 - Testing if a graph is a bicliqueDownload
41Lesson 6 - Testing bipartitenessDownload
42Lesson 1 - Property testing and random walk algorithmsDownload
43Lesson 2 - Testing if a graph is bipartite (using random walks)Download
44Lesson 3 - Graph streaming algorithms: IntroductionDownload
45Lesson 4 - Graph streaming algorithms: MatchingDownload
46Lesson 5 - Graph streaming algorithms: Graph sparsificationDownload
47Lesson 1 - MapReduceDownload
48Lesson 2 - K-Machine Model (aka Pregel Model)Download

Sl.No Chapter Name English
1Lesson 1 - Basic definitionsDownload
Verified
2Lesson 2 - Conditional probabilityDownload
Verified
3Lesson 3 - Example problemsDownload
Verified
4Lesson 4 - Karger's mincut algorithmDownload
Verified
5Lesson 5 - Analysis of Karger's mincut algorithmDownload
Verified
6Lesson 6 - Random variablesDownload
Verified
7Lesson 7 - Randomized quicksortDownload
Verified
8Problem solving video - The rich get richerDownload
Verified
9Problem solving video - Monty Hall problemDownload
Verified
10Lesson 1 - Bernoulli, Binomial, and Geometric distributionsDownload
Verified
11Lesson 2 - Tail BoundsDownload
Verified
12Lesson 3 - Application of Chernoff boundDownload
Verified
13Lesson 4 - Application of Chebyshev's inequalityDownload
Verified
14Lesson 1 - Intro to Big Data AlgorithmsDownload
Verified
15Lesson 2 - SAT ProblemDownload
Verified
16Lesson 3 - Classification of StatesDownload
Verified
17Lesson 4 - Stationary Distribution of a Markov ChainDownload
Verified
18Lesson 5 - Celebrities Case StudyDownload
Verified
19Lesson 6 - Random Walks on Undirected GraphsDownload
Verified
20Lesson 7 - Intro to Streaming, Morris AlgorithmDownload
Verified
21Lesson 8 - Reservoir SamplingDownload
Verified
22Lesson 9 - Approximate MedianDownload
Verified
23Lesson 1 : OverviewDownload
Verified
24Lesson 2 : Balls, bins, hashingDownload
Verified
25Lesson 3 : Chain hashing, SUHA, Power of Two choicesDownload
Verified
26Lesson 4 : Bloom filterDownload
Verified
27Lesson 5 : Pairwise independenceDownload
Verified
28Lesson 6 : Estimating expectation of continuous functionDownload
Verified
29Lesson 1 - Universal hash functionsDownload
Verified
30Lesson 2 - Perfect hashingDownload
Verified
31Lesson 3 - Count-min filter for heavy hitters in data streamsDownload
Verified
32Problem solving video - Doubly Stochastic Transition MatrixDownload
Verified
33Problem solving video - Random Walks on Linear StructuresDownload
Verified
34Problem solving video - Lollipop GraphDownload
Verified
35Problem solving video - Cat And MouseDownload
Verified
36Lesson 1 - Estimating frequency momentsDownload
Verified
37Lesson 2 - Property testing frameworkDownload
Verified
38Lesson 3 - Testing ConnectivityDownload
Verified
39Lesson 4 - Enforce & Test IntroductionDownload
Verified
40Lesson 5 - Testing if a graph is a bicliqueDownload
Verified
41Lesson 6 - Testing bipartitenessDownload
Verified
42Lesson 1 - Property testing and random walk algorithmsDownload
Verified
43Lesson 2 - Testing if a graph is bipartite (using random walks)Download
Verified
44Lesson 3 - Graph streaming algorithms: IntroductionDownload
Verified
45Lesson 4 - Graph streaming algorithms: MatchingDownload
Verified
46Lesson 5 - Graph streaming algorithms: Graph sparsificationDownload
Verified
47Lesson 1 - MapReduceDownload
Verified
48Lesson 2 - K-Machine Model (aka Pregel Model)Download
Verified


Sl.No Language Book link
1EnglishDownload
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available