| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Lecture 01 : Introduction to Maximum Flow | Download |
| 2 | Lecture 02 : Ford - Fulkerson Method | Download |
| 3 | Lecture 03 : Edmond - Karp Algorithm | Download |
| 4 | Lecture 04 : Edmond - Karp Algorithm (Contd.) | Download |
| 5 | Lecture 05 : Flow Decomposition | Download |
| 6 | Lecture 06 : Maximum Bipartite Matching, Fattest Augmenting Path | Download |
| 7 | Lecture 07 : Karger's Algorithm | Download |
| 8 | Lecture 08 : Augmenting Path | Download |
| 9 | Lecture 09 : Edmonds Blossom Algorithm | Download |
| 10 | Lecture 10 : Edmond - Karp Algorithm (Contd.) | Download |
| 11 | Lecture 11: Introduction to Randomized Algorithm | Download |
| 12 | Lecture 12: Polynomial Identity Testing | Download |
| 13 | Lecture 13: Perfect Bipartite Matching, Randomized Quicksort | Download |
| 14 | Lecture 14: Concentration Inequalities: Markov, Chebyshev, Chernoff | Download |
| 15 | Lecture 15: Proof of Chernoff Bound | Download |
| 16 | Lecture 21: Markov Chain, Periodicity, Stationary Distribution | Download |
| 17 | Lecture 22: Mixing Time, Reversible Markov Chain | Download |
| 18 | Lecture 23: Metropolis Algorithm, Markov Chain on Independent Sets | Download |
| 19 | Lecture 24: Random Walk on Cycles | Download |
| 20 | Lecture 25: Shuffling Cards | Download |
| 21 | Lecture 26: Monte Carlo Method, Hitting Time, Cover Time | Download |
| 22 | Lecture 27: DNF Counting | Download |
| 23 | Lecture 28: DNF Counting (Contd.) | Download |
| 24 | Lecture 29: Counting Independent Sets of a Graph | Download |
| 25 | Lecture 30: Counting Independent Sets of a Graph (Contd.) | Download |
| 26 | Lecture 31: Introduction of NP, co-NP, and P | Download |
| 27 | Lecture 32: Turing Reduction, Karp Reduction | Download |
| 28 | Lecture 33: NP - Completeness of 3SAT | Download |
| 29 | Lecture 34: NP - Completeness of Independent Set | Download |
| 30 | Lecture 35: NP - Completeness of vertex cover and clique | Download |
| 31 | Lecture 36: NP - Completeness of 3 - coloring | Download |
| 32 | Lecture 37: NP - Completeness of Subset sum and Knapsack | Download |
| 33 | Lecture 38: NP - Completeness of set cover, Weak and Strong NP - completeness | Download |
| 34 | Lecture 39: Self Reduction | Download |
| 35 | Lecture 40: Randomized Approximation Algorithm | Download |
| 36 | Lecture 41: Derandomization | Download |
| 37 | Lecture 42: Travelling Salesman Problem | Download |
| 38 | Lecture 43: 2 - Factor Approximation Algorithm for Metric TSP | Download |
| 39 | Lecture 44: 1.5 - Factor Approximation Algorithm for Metric TSP | Download |
| 40 | Lecture 45: Approximation Algorithm for Set Cover | Download |
| 41 | Lecture 46: FPTAS for Knapsack | Download |
| 42 | Lecture 47: Introduction to Linear Program | Download |
| 43 | Lecture 48: Introduction to Linear Program (Contd.,) | Download |
| 44 | Lecture 49: Dual Fitting | Download |
| 45 | Lecture 50: Dual Fitting (Contd.) | Download |
| 46 | Lecture 51 : Dual Fitting | Download |
| 47 | Lecture 52 : Set Cover using LP rounding | Download |
| 48 | Lecture 53 : Vertex Cover using reduction to set cover | Download |
| 49 | Lecture 54 : Vertex Cover LP | Download |
| 50 | Lecture 55 : Randomized Rounding | Download |
| 51 | Lecture 56: Primal Dual Scheme | Download |
| 52 | Lecture 57: Introduction to Parameterized Algorithm | Download |
| 53 | Lecture 58: Faster FPT Algorithm for Vertex Cover | Download |
| 54 | Lecture 59: Introduction to Kernelization | Download |
| 55 | Lecture 60: Linear Programming Based Kernels | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Lecture 01 : Introduction to Maximum Flow | PDF unavailable |
| 2 | Lecture 02 : Ford - Fulkerson Method | PDF unavailable |
| 3 | Lecture 03 : Edmond - Karp Algorithm | PDF unavailable |
| 4 | Lecture 04 : Edmond - Karp Algorithm (Contd.) | PDF unavailable |
| 5 | Lecture 05 : Flow Decomposition | PDF unavailable |
| 6 | Lecture 06 : Maximum Bipartite Matching, Fattest Augmenting Path | PDF unavailable |
| 7 | Lecture 07 : Karger's Algorithm | PDF unavailable |
| 8 | Lecture 08 : Augmenting Path | PDF unavailable |
| 9 | Lecture 09 : Edmonds Blossom Algorithm | PDF unavailable |
| 10 | Lecture 10 : Edmond - Karp Algorithm (Contd.) | PDF unavailable |
| 11 | Lecture 11: Introduction to Randomized Algorithm | PDF unavailable |
| 12 | Lecture 12: Polynomial Identity Testing | PDF unavailable |
| 13 | Lecture 13: Perfect Bipartite Matching, Randomized Quicksort | PDF unavailable |
| 14 | Lecture 14: Concentration Inequalities: Markov, Chebyshev, Chernoff | PDF unavailable |
| 15 | Lecture 15: Proof of Chernoff Bound | PDF unavailable |
| 16 | Lecture 21: Markov Chain, Periodicity, Stationary Distribution | PDF unavailable |
| 17 | Lecture 22: Mixing Time, Reversible Markov Chain | PDF unavailable |
| 18 | Lecture 23: Metropolis Algorithm, Markov Chain on Independent Sets | PDF unavailable |
| 19 | Lecture 24: Random Walk on Cycles | PDF unavailable |
| 20 | Lecture 25: Shuffling Cards | PDF unavailable |
| 21 | Lecture 26: Monte Carlo Method, Hitting Time, Cover Time | PDF unavailable |
| 22 | Lecture 27: DNF Counting | PDF unavailable |
| 23 | Lecture 28: DNF Counting (Contd.) | PDF unavailable |
| 24 | Lecture 29: Counting Independent Sets of a Graph | PDF unavailable |
| 25 | Lecture 30: Counting Independent Sets of a Graph (Contd.) | PDF unavailable |
| 26 | Lecture 31: Introduction of NP, co-NP, and P | PDF unavailable |
| 27 | Lecture 32: Turing Reduction, Karp Reduction | PDF unavailable |
| 28 | Lecture 33: NP - Completeness of 3SAT | PDF unavailable |
| 29 | Lecture 34: NP - Completeness of Independent Set | PDF unavailable |
| 30 | Lecture 35: NP - Completeness of vertex cover and clique | PDF unavailable |
| 31 | Lecture 36: NP - Completeness of 3 - coloring | PDF unavailable |
| 32 | Lecture 37: NP - Completeness of Subset sum and Knapsack | PDF unavailable |
| 33 | Lecture 38: NP - Completeness of set cover, Weak and Strong NP - completeness | PDF unavailable |
| 34 | Lecture 39: Self Reduction | PDF unavailable |
| 35 | Lecture 40: Randomized Approximation Algorithm | PDF unavailable |
| 36 | Lecture 41: Derandomization | PDF unavailable |
| 37 | Lecture 42: Travelling Salesman Problem | PDF unavailable |
| 38 | Lecture 43: 2 - Factor Approximation Algorithm for Metric TSP | PDF unavailable |
| 39 | Lecture 44: 1.5 - Factor Approximation Algorithm for Metric TSP | PDF unavailable |
| 40 | Lecture 45: Approximation Algorithm for Set Cover | PDF unavailable |
| 41 | Lecture 46: FPTAS for Knapsack | PDF unavailable |
| 42 | Lecture 47: Introduction to Linear Program | PDF unavailable |
| 43 | Lecture 48: Introduction to Linear Program (Contd.,) | PDF unavailable |
| 44 | Lecture 49: Dual Fitting | PDF unavailable |
| 45 | Lecture 50: Dual Fitting (Contd.) | PDF unavailable |
| 46 | Lecture 51 : Dual Fitting | PDF unavailable |
| 47 | Lecture 52 : Set Cover using LP rounding | PDF unavailable |
| 48 | Lecture 53 : Vertex Cover using reduction to set cover | PDF unavailable |
| 49 | Lecture 54 : Vertex Cover LP | PDF unavailable |
| 50 | Lecture 55 : Randomized Rounding | PDF unavailable |
| 51 | Lecture 56: Primal Dual Scheme | PDF unavailable |
| 52 | Lecture 57: Introduction to Parameterized Algorithm | PDF unavailable |
| 53 | Lecture 58: Faster FPT Algorithm for Vertex Cover | PDF unavailable |
| 54 | Lecture 59: Introduction to Kernelization | PDF unavailable |
| 55 | Lecture 60: Linear Programming Based Kernels | PDF unavailable |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Not Available |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |