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# Design and Analysis of algorithms (DAA)

### Syllabus

L-1.1: Introduction to Algorithm & Syllabus Discussion for GATE/NET & Placements Preparation | DAA.
L-1.2: What is Algorithm | How to Analyze an Algorithm | Priori vs Posteriori Analysis | DAA.
L-1.3: Asymptotic Notations | Big O | Big Omega | Theta Notations | Most Imp Topic Of Algorithm.
L-1.4: Various Properties of Asymptotic Notation with Example | Algorithm | DAA.
L-1.5: Comparison of Various Time Complexities | Different types in Increasing Order| Must Watch.
L-1.6: Time Complexities of all Searching and Sorting Algorithms in 10 minute | GATE & other Exams.
L-1.7: Question#1 on Comparison of Various Time Complexities | GATE Questions.
L-1.8: Question#2 on Comparison of Various Time Complexities | GATE Questions.
L-2.1: What is Recurrence Relation| How to Write Binary Search Recurrence Relation|How we Solve them.
L-2.2: How to Solve Recurrence Relation using Substitution Method | Question#2 | Algorithm.
L-2.3: What is Substitution Method| How to Solve Recurrence Relation using Substitution Method.
L-2.4: How Master Theorem Solve Recurrence Relations| Example#1 | All Cases Explained with Example.
L-2.5: How to Solve Recurrence Relation Using Master Method | Example-2 | Master Theorem | Algorithm.
L-3.0: Divide and Conquer | Algorithm.
L-3.1: How Quick Sort Works | Performance of Quick Sort with Example | Divide and Conquer.
L-3.2: Performance of Quick Sort | Worst Case Time Complexity with Example | Algorithm.
L-3.3: Imp. Question on Merge Sort | Divide and Conquer | Algorithm.
L-3.4: How Bubble Sort Works | Performance of Bubble Sort | All Imp Points with Example | Algorithm.
L-3.5: Insertion Sort | Time Complexity Analysis | Stable Sort | Inplace Sorting.
L-3.6: Selection Sort | Time Complexity(Best, Avg & Worst) Analysis | Stable or Not | Inplace or Not.
L-3.7: Introduction to Trees (Binary Tree, Almost Complete Binary Tree, Full BT, Complete BT, BST).
L-3.8: Introduction to Heap Tree with examples | Max Min Heap.
L-3.9: Insertion in Heap Tree | Max-Heap & Min-Heap Creation | Time Complexities.
L-3.10: Imp Question on Max Heap | GATE Question on Max/Min Heap | Algorithm.
L-3.11: Build Heap in O(n) time complexity | Heapify Method | Full Derivation with example.
L-3.12: Deletion in Heap tree | Time complexity.
L-3.13: Heap sort with Example | Heapify Method.
L-4.1: Introduction to Greedy Techniques With Example | What is Greedy Techniques.
L-4.2: Knapsack Problem With Example| Greedy Techniques| Algorithm.
L-4.3: Huffman Coding Algorithm in Hindi with Example | Greedy Techniques(Algorithm).
L-4.4: Huffman Coding Question in Greedy Technique | Imp Question for all competitive exams.
L-4.5: Job Sequencing Algorithm with Example | Greedy Techniques.
L-4.6: Optimal Merge Pattern using Greedy Method in Hindi | Algorithm.
L-4.7: What is Spanning Tree with Examples in Hindi | Algorithm.
L-4.8: Kruskal Algorithm for Minimum Spanning Tree in Hindi | Algorithm.
L-4.9: Prim's Algorithm for Minimum Cost Spanning Tree | Prims vs Kruskal.
L-4.10: Dijkstra's Algorithm - Single Source Shortest Path - Greedy Method.
L-4.11: Dijkstra's Algorithm Analysis | Time Complexity | Pseudocode Explanation.
L-4.12: Why does Dijkstra fail on Negative Weights?? Full Explanation with examples.
L-4.13: Bellman Ford Algorithm | Dijkstra's Vs Bellman Ford | Single Source Shortest Path.
L-4.14: Bellman Ford pseudo code and Time complexity | Single Source Shortest Path.
L-5.1: Introduction to Dynamic Programming | Greedy Vs Dynamic Programming | Algorithm(DAA).
L-5.2: 0/1 Knapsack failed using Greedy approach.
L-5.3: 0/1 Knapsack Problem |Dynamic Programming |Recursive Equation |Recursion Tree|Time Complexity.
L-5.4: Traveling Salesman Problem | Dynamic Programming.
Sum of Subsets Problem | Dynamic Programming.
Multistage Graph | Dynamic Programming.
L-6.1: What is hashing with example | Hashing in data structure.
L-6.2: Collision Resolution Techniques in Hashing | What are the collision resolution techniques?.
L-6.3: Chaining in Hashing | What is chaining in hashing with examples.
L-6.4: Linear Probing in Hashing with example.
L-6.5: Imp Question on Hashing | Linear Probing for Collision in Hash Table | GATE Questions.
L-6.6: Quadratic Probing in Hashing with example.
L-6.7: Double Hashing | Collision Resolution Technique.
Recurrence Relation T(n)=T(âˆšn)+logn | Master Theorem.
Introduction to All Pair Shortest Path (Floyd Warshall Algorithm).
Floyd Warshall Working with example | All Pair Shortest Path Algorithm.
Floyd Warshall Time & Space complexity | All Pair Shortest Path.

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