Student will learn :
- Problem Solving Techniques.
- Time complexity and Space complexity analysis.
- Divide and Conquer Strategy.
- Greedy Approach.
- Dynamic Programming.
- Searching Algorithms.
- Sorting Algorithms.
Course Curriculum
- Aymptotic Notations
- Time Complexity
- Master Theorem
- Spanning Trees
- Spanning Trees Introduction.
- Spanning Trees Properties Continuation.
- Minimum Spanning Trees Definition and Algorithms Introduction
- Krushkal’s Algorithm for finding Minimum Spanning Trees.
- Krushkal’s Algorithm for finding Minimum Spanning Trees Continuation
- Krushkal’s Algorithm for finding Minimum Spanning Trees – Time Complexity.
- Prim’s Algorithm for finding Minimum Spanning Tree and Time Complexity.
- Sorting Algorithms
- 1. Bubble Sort : Understanding Example
- 1. Bubble Sort : Time Complexity
- 1. Bubble Sort : Algorithm
- 1. Bubble Sort : Reducing Time Complexity
- Code : Bubble Sort
- 2. Insertion Sort : Understanding Example
- 2. Insertion Sort : Algorithm
- 2. Insertion Sort : Time Complexity
- Code : Insertion Sort
- 3. Selection Sort : Understanding Example
- 3. Selection Sort : Algorithm
- 3. Selection Sort : Time Complexity
- Code
- Heap Sort : Understanding with Example
- Heap Sort : Time Complexity
- Searching Algorithms
- Matrix Chain Multiplication
- Greedy Method
- Job Sequencing Problem : Theory
- Job Sequencing Problem : Example 1
- Job Sequencing Problem : Example 2
- Knapsack Problem : Theory
- Knapsack Problem : Example – Greedy about Weight, Profit and Unit Cost.
- Optimal Merge Pattern : Theory
- Optimal Merge Pattern : Example
- Dynamic Programming : Introduction
- Multistage Graph
- Travelling Salesperson Problem Cop
- All Pairs Shortest Path Problem
