Cracking the Complexity 🔥: A Comprehensive Guide to Big O Notation Time Complexity (with Animation)
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From Novice to Ninja 🚀:
From Novice to Ninja 🚀: Mastering Big O Notation Time Complexity for Coding Interviews💻
In this comprehensive tutorial on Big O notation and time complexity, we delve into the fundamental concepts that govern the efficiency of algorithms. Understanding time complexity is crucial for acing coding interviews at top tech companies like Amazon, Microsoft, and Google. Whether you're a beginner in programming or preparing for a challenging coding interview, this video is the ultimate guide to mastering Big O notation and analyzing time complexity.
Timestamps: 🕗
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00:00:00 Introduction
00:00:26 Types Of Complexity
00:00:47 Why Time Complexity is Important
00:01:30 Measurement of time complexity of the algorithm
00:02:44 General rules for Big O
00:04:18 Constant time complexity - O(1)
00:08:03 Linear Time complexity - O(n)
00:14:00 Quadratic Time complexity - O(n^2)
00:17:02 Logarithmic Time complexity - O(log n)
00:22:50 Linearithmic Time complexity - O(n log n)
00:23:59 Exponential Time complexity - O(2^n)
00:25:00 Different terms for input
00:26:01 Big O time complexity graph
00:27:45 Choosing the right algorithm
🔍 Topics Covered:
---------------------------------
🎯What is Big O notation and why is it important in algorithm analysis?
🎯Understanding time complexity and its significance in evaluating the efficiency of algorithms.
🎯Exploring various types of time complexities, such as constant time (O(1)), linear time (O(n)), logarithmic time (O(log n)), and more.
🎯How to analyze the time complexity of common data structures and algorithms.
🎯Practical tips and tricks for optimizing algorithms to achieve better time complexity.
💻 💻 💯 Whether you're studying data structures and algorithms, preparing for coding interviews, or simply curious about how to assess the efficiency of algorithms, this video will equip you with the knowledge and techniques to navigate the world of Big O notation and time complexity. Don't miss out on this valuable resource that will boost your programming skills and give you a competitive edge in your coding journey.
🎥 Watch more programming tutorials and coding interview tips on my channel to enhance your skills and ace your next coding interview!
big o notation, time complexity, time complexity of the algorithm, big o notation tutorial, big o notation explained, time complexity tutorial, algorithms, big o complexity, big o notation in data structure, what is big o notation, amazon coding interview, microsoft coding interview, google coding interview, programming interview, coding interview, big oh notation in data structure, data structures and algorithms, big o, big oh, time complexity in data structure
#BigONotation #TimeComplexity #AlgorithmAnalysis #CSDojo #CodingInterview #DataStructuresAndAlgorithms
Recommended Youtube channel: cs dojo, CodeWithHarry, freeCodeCamp.org, NeetCode,
Bro Code, Abdul Bari
By - Sahadat Husain
-----------------------------------------------------------------
✅ Website - https://devsahadat.com
✅ Email - [email protected]
✅ Phone - 01738309749
In this comprehensive tutorial on Big O notation and time complexity, we delve into the fundamental concepts that govern the efficiency of algorithms. Understanding time complexity is crucial for acing coding interviews at top tech companies like Amazon, Microsoft, and Google. Whether you're a beginner in programming or preparing for a challenging coding interview, this video is the ultimate guide to mastering Big O notation and analyzing time complexity.
Timestamps: 🕗
----------------------------------
00:00:00 Introduction
00:00:26 Types Of Complexity
00:00:47 Why Time Complexity is Important
00:01:30 Measurement of time complexity of the algorithm
00:02:44 General rules for Big O
00:04:18 Constant time complexity - O(1)
00:08:03 Linear Time complexity - O(n)
00:14:00 Quadratic Time complexity - O(n^2)
00:17:02 Logarithmic Time complexity - O(log n)
00:22:50 Linearithmic Time complexity - O(n log n)
00:23:59 Exponential Time complexity - O(2^n)
00:25:00 Different terms for input
00:26:01 Big O time complexity graph
00:27:45 Choosing the right algorithm
🔍 Topics Covered:
---------------------------------
🎯What is Big O notation and why is it important in algorithm analysis?
🎯Understanding time complexity and its significance in evaluating the efficiency of algorithms.
🎯Exploring various types of time complexities, such as constant time (O(1)), linear time (O(n)), logarithmic time (O(log n)), and more.
🎯How to analyze the time complexity of common data structures and algorithms.
🎯Practical tips and tricks for optimizing algorithms to achieve better time complexity.
💻 💻 💯 Whether you're studying data structures and algorithms, preparing for coding interviews, or simply curious about how to assess the efficiency of algorithms, this video will equip you with the knowledge and techniques to navigate the world of Big O notation and time complexity. Don't miss out on this valuable resource that will boost your programming skills and give you a competitive edge in your coding journey.
🎥 Watch more programming tutorials and coding interview tips on my channel to enhance your skills and ace your next coding interview!
big o notation, time complexity, time complexity of the algorithm, big o notation tutorial, big o notation explained, time complexity tutorial, algorithms, big o complexity, big o notation in data structure, what is big o notation, amazon coding interview, microsoft coding interview, google coding interview, programming interview, coding interview, big oh notation in data structure, data structures and algorithms, big o, big oh, time complexity in data structure
#BigONotation #TimeComplexity #AlgorithmAnalysis #CSDojo #CodingInterview #DataStructuresAndAlgorithms
Recommended Youtube channel: cs dojo, CodeWithHarry, freeCodeCamp.org, NeetCode,
Bro Code, Abdul Bari
By - Sahadat Husain
-----------------------------------------------------------------
✅ Website - https://devsahadat.com
✅ Email - [email protected]
✅ Phone - 01738309749
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