Design and Analysis of Algorithms

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

Total learning: 59 lessons Time: 100 weeks

Aymptotic Notations 10
- Lecture1.1
  Asymptotic Notations : Introduction.
- Lecture1.2
  Big Oh (O) : Example – 1
- Lecture1.3
  Big Oh (O) : Example – 2
- Lecture1.4
  Big Oh (O) : Example – 3
- Lecture1.5
  Big Oh (O) : Multiplication and Addition
- Lecture1.6
  Big Omega (Ω)
- Lecture1.7
  Theta (Θ)
- Lecture1.8
  Properties
- Lecture1.9
  Example : 4
- Lecture1.10
  Examples Copy
Time Complexity 5
- Lecture2.1
  Introduction Copy
- Lecture2.2
  Time Complexity Calculation for Simple Loops – 1
- Lecture2.3
  Time Complexity Calculation for Simple Loops – 2
- Lecture2.4
  Time Complexity Calculation for Nested Loops – 1
- Lecture2.5
  Time Complexity Calculation for Nested Loops – 2
Master Theorem 4
- Lecture3.1
  Master Theorem Introduction.
- Lecture3.2
  Master Theorem Formula discussion.
- Lecture3.3
  Master Theorem Examples – 1
- Lecture3.4
  Master Theorem Examples – 2
Spanning Trees 7
- Lecture4.1
  Spanning Trees Introduction.
- Lecture4.2
  Spanning Trees Properties Continuation.
- Lecture4.3
  Minimum Spanning Trees Definition and Algorithms Introduction
- Lecture4.4
  Krushkal’s Algorithm for finding Minimum Spanning Trees.
- Lecture4.5
  Krushkal’s Algorithm for finding Minimum Spanning Trees Continuation
- Lecture4.6
  Krushkal’s Algorithm for finding Minimum Spanning Trees – Time Complexity.
- Lecture4.7
  Prim’s Algorithm for finding Minimum Spanning Tree and Time Complexity.
Sorting Algorithms 15
- Lecture5.1
  1. Bubble Sort : Understanding Example
- Lecture5.2
  1. Bubble Sort : Time Complexity
- Lecture5.3
  1. Bubble Sort : Algorithm
- Lecture5.4
  1. Bubble Sort : Reducing Time Complexity
- Lecture5.5
  Code : Bubble Sort
- Lecture5.6
  2. Insertion Sort : Understanding Example
- Lecture5.7
  2. Insertion Sort : Algorithm
- Lecture5.8
  2. Insertion Sort : Time Complexity
- Lecture5.9
  Code : Insertion Sort
- Lecture5.10
  3. Selection Sort : Understanding Example
- Lecture5.11
  3. Selection Sort : Algorithm
- Lecture5.12
  3. Selection Sort : Time Complexity
- Lecture5.13
  Code
- Lecture5.14
  Heap Sort : Understanding with Example
- Lecture5.15
  Heap Sort : Time Complexity
Searching Algorithms 6
- Lecture6.1
  Linear Search
- Lecture6.2
  Code : Linear Search
- Lecture6.3
  Binary Search : Understanding with Example
- Lecture6.4
  Binary Search : Iterative and Recursive Algorithms
- Lecture6.5
  Code : Binary Search – Iterative
- Lecture6.6
  Code : Binary Search – Recursive
Matrix Chain Multiplication 1
- Lecture7.1
  Matrix Chain Multiplication
Greedy Method 11
- Lecture8.1
  Job Sequencing Problem : Theory
- Lecture8.2
  Job Sequencing Problem : Example 1
- Lecture8.3
  Job Sequencing Problem : Example 2
- Lecture8.4
  Knapsack Problem : Theory
- Lecture8.5
  Knapsack Problem : Example – Greedy about Weight, Profit and Unit Cost.
- Lecture8.6
  Optimal Merge Pattern : Theory
- Lecture8.7
  Optimal Merge Pattern : Example
- Lecture8.8
  Dynamic Programming : Introduction
- Lecture8.9
  Multistage Graph
- Lecture8.10
  Travelling Salesperson Problem Cop
- Lecture8.11
  All Pairs Shortest Path Problem

Atchyut Kumar is popular programming and GATE CS/IT instructor. He did his Masters from National Institute of Technology-Calicut. He is GATE CS/IT top ranker with 99.97 percentile. He have three years of experience in database development and 7+ years years as GATE faculty. Totally, He have 11+ Years of overall experience in Teaching/research/Industry where trained over 30000 students in classroom and online courses. He is expert in problem solving techniques, algorithms, competitive programming. Most of his ex-students are working in Amazon, Samsung, Oracle, Google, Adobe and more and some of them pursuing higher studies like MS, M.Tech or Ph.D.