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Complexity Algorithms

Track :

Programming

Lessons no : 189

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What will you learn in this course?
  • Understand and analyze algorithm complexity using Big O notation for various algorithms including linear and binary search
  • Apply Big O notation to evaluate and compare algorithm efficiency in real-world scenarios
  • Identify different types of algorithm complexities such as linear, logarithmic, quadratic, and exponential
  • Develop skills to optimize algorithms based on their time complexity for improved performance
  • Interpret algorithm performance metrics to make informed decisions in software development
  • Utilize complexity analysis to troubleshoot and improve existing algorithms in practical applications
  • Differentiate between best, average, and worst-case complexities in algorithm analysis
  • Implement algorithms with optimal time complexity for large-scale data processing and computational tasks
  • Assess the impact of algorithm complexity on system scalability and resource management
  • Design algorithms with efficient complexity to enhance application speed and responsiveness
  • Evaluate the trade-offs between algorithm complexity and implementation complexity
  • Apply complexity analysis techniques to real-world problems in data structures and algorithms
  • Use Big O notation to predict algorithm behavior and performance in different input scenarios
  • Analyze the complexity of recursive and iterative algorithms for better optimization
  • Compare the efficiency of different algorithms solving the same problem using complexity metrics
  • Integrate complexity analysis into software development lifecycle for performance tuning

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Lessons | 189
Intro to Algorithms Georgia Tech Computability Complexity Theory Algorithms
00:01:50

Intro to Algorithms Georgia Tech Computability Complexity Theory Algorithms
Introduction Georgia Tech Computability Complexity Theory Algorithms
00:00:37

Introduction Georgia Tech Computability Complexity Theory Algorithms
Lesson Plan Georgia Tech Computability Complexity Theory Algorithms
00:00:42

Lesson Plan Georgia Tech Computability Complexity Theory Algorithms
Optimal Similar Substructure GT Computability Complexity Theory Algorithms
00:04:29

Optimal Similar Substructure GT Computability Complexity Theory Algorithms
Edit Distance Problem Georgia Tech Computability Complexity Theory Algorithms
00:01:33

Edit Distance Problem Georgia Tech Computability Complexity Theory Algorithms
Sequence Alignment Cost Quiz GT Computability Complexity Theory Algorithms
00:00:14

Sequence Alignment Cost Quiz GT Computability Complexity Theory Algorithms
Sequence Alignment Cost Solution GT Computability Complexity Theory Algorithms
00:00:14

Sequence Alignment Cost Solution GT Computability Complexity Theory Algorithms
Prefix Substructure Georgia Tech Computability Complexity Theory Algorithms
00:02:00

Prefix Substructure Georgia Tech Computability Complexity Theory Algorithms
Sequence Alignment Algorithm GT Computability Complexity Theory Algorithms
00:01:26

Sequence Alignment Algorithm GT Computability Complexity Theory Algorithms
Sequence Alignment Exercise GT Computability Complexity Theory Algorithms
00:00:27

Sequence Alignment Exercise GT Computability Complexity Theory Algorithms
Sequence Alignment Solution GT Computability Complexity Theory Algorithms
00:01:29

Sequence Alignment Solution GT Computability Complexity Theory Algorithms
Sequence Alignment Summary GT Computability Complexity Theory Algorithms
00:00:52

Sequence Alignment Summary GT Computability Complexity Theory Algorithms
Chain Matrix Multiplication Georgia Tech Computability Complexity Theory Algorithms
00:02:15

Chain Matrix Multiplication Georgia Tech Computability Complexity Theory Algorithms
Subchain Substructure Georgia Tech Computability Complexity Theory Algorithms
00:01:36

Subchain Substructure Georgia Tech Computability Complexity Theory Algorithms
CMM Algorithm Georgia Tech Computability Complexity Theory Algorithms
00:02:21

CMM Algorithm Georgia Tech Computability Complexity Theory Algorithms
CMM Exercise Quiz Georgia Tech Computability Complexity Theory Algorithms
00:00:24

CMM Exercise Quiz Georgia Tech Computability Complexity Theory Algorithms
CMM Exercise Solution Georgia Tech Computability Complexity Theory Algorithms
00:02:36

CMM Exercise Solution Georgia Tech Computability Complexity Theory Algorithms
CMM Summary Georgia Tech Computability Complexity Theory Algorithms
00:00:49

CMM Summary Georgia Tech Computability Complexity Theory Algorithms
All Pairs Shortest Path Georgia Tech Computability Complexity Theory Algorithms
00:02:37

All Pairs Shortest Path Georgia Tech Computability Complexity Theory Algorithms
Shortest Path Substructure GT Computability Complexity Theory Algorithms
00:03:43

Shortest Path Substructure GT Computability Complexity Theory Algorithms
The Floyd Warshall Algorithm GT Computability Complexity Theory Algorithms
00:01:50

The Floyd Warshall Algorithm GT Computability Complexity Theory Algorithms
Floyd Warshall Algorithm Exercise GT Computability Complexity Theory Algorithms
00:00:24

Floyd Warshall Algorithm Exercise GT Computability Complexity Theory Algorithms
Floyd Warshall Algorithm Georgia Tech Computability Complexity Theory Algorithms
00:01:59

Floyd Warshall Algorithm Georgia Tech Computability Complexity Theory Algorithms
All Pairs Summary Georgia Tech Computability Complexity Theory Algorithms
00:00:38

All Pairs Summary Georgia Tech Computability Complexity Theory Algorithms
Transitive Closure Georgia Tech Computability Complexity Theory Algorithms
00:02:12

Transitive Closure Georgia Tech Computability Complexity Theory Algorithms
Dynamic Programming Conclusion GT Computability Complexity Theory Algorithms
00:01:14

Dynamic Programming Conclusion GT Computability Complexity Theory Algorithms
Introduction Georgia Tech Computability Complexity Theory Algorithms
00:01:18

Introduction Georgia Tech Computability Complexity Theory Algorithms
Prerequisites Georgia Tech Computability Complexity Theory Algorithms
00:00:29

Prerequisites Georgia Tech Computability Complexity Theory Algorithms
Convolution Georgia Tech Computability Complexity Theory Algorithms
00:03:00

Convolution Georgia Tech Computability Complexity Theory Algorithms
Representations of Polynomials GT Computability Complexity Theory Algorithms
00:01:34

Representations of Polynomials GT Computability Complexity Theory Algorithms
Multiplying Polynomials Georgia Tech Computability Complexity Theory Algorithms
00:01:04

Multiplying Polynomials Georgia Tech Computability Complexity Theory Algorithms
Multiplication Exercise Quiz GT Computability Complexity Theory Algorithms
00:00:16

Multiplication Exercise Quiz GT Computability Complexity Theory Algorithms
Multiplication Exercise Solution GT Computability Complexity Theory Algorithms
00:01:01

Multiplication Exercise Solution GT Computability Complexity Theory Algorithms
Multiplying Polynomials Continued GT Computability Complexity Theory Algorithms
00:01:32

Multiplying Polynomials Continued GT Computability Complexity Theory Algorithms
Divide and Conquer Inspiration GT Computability Complexity Theory Algorithms
00:02:48

Divide and Conquer Inspiration GT Computability Complexity Theory Algorithms
Roots of Unity Georgia Tech Computability Complexity Theory Algorithms
00:04:41

Roots of Unity Georgia Tech Computability Complexity Theory Algorithms
FFT Example Georgia Tech Computability Complexity Theory Algorithms
00:01:16

FFT Example Georgia Tech Computability Complexity Theory Algorithms
FFT Exercise Quiz Georgia Tech Computability Complexity Theory Algorithms
00:00:18

FFT Exercise Quiz Georgia Tech Computability Complexity Theory Algorithms
FFT Exercise Solution Georgia Tech Computability Complexity Theory Algorithms
00:01:23

FFT Exercise Solution Georgia Tech Computability Complexity Theory Algorithms
FFT Algorithm Georgia Tech Computability Complexity Theory Algorithms
00:01:58

FFT Algorithm Georgia Tech Computability Complexity Theory Algorithms
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When we analyse an algorithm, we use a notation to represent its time complexity and that notation is Big O notation. For Example: time complexity for Linear search can be represented as O(n) and O(log n) for Binary search (where, n and log(n) are the number of operations) .