Recursion-12 | Time Complexity (Theory)

Telegram Channel : https://t.me/ctobhaiya_tg Instagram: https://www.instagram.com/ctobhaiya Linkedin: https://www.linkedin.com/in/anuj-kumar-a-k-a-cto-bhaiya-on-youtube-9a188968 Github: https://github.com/team-codebug/babua-dsa-patterns-course Support me 🙌🏻: https://www.buymeacoffee.com/anuj.baranwal.1994 Leetcode: X Github Repo: https://github.com/team-codebug/leetcode Notes: https://github.com/team-codebug/leetcode/blob/main/DSA_In_90Days/13_Recursion/Recursion_12_Time_Complexity.svg 3 Months DSA for Placements! 🚀 Beginner to Advanced Playlist 🧠 Understanding Time Complexity in Recursion – Simplified! In this video, we break down how to analyze time complexity in recursive algorithms step by step. Using real examples like the Fibonacci function and factorial, you'll learn how to: ✅ Identify the number of recursive calls ✅ Use recurrence relations ✅ Visualize execution trees ✅ Understand why some recursive functions take O(n) while others explode to O(2ⁿ) ✅ Learn how memoization optimizes time complexity Whether you're preparing for coding interviews or trying to master recursion, this video will give you a clear and practical understanding of time complexity in recursive code. 📌 Don't forget to like, comment, and subscribe for more DSA concepts explained simply! #TimeComplexity #RecursionExplained #DSAforBeginners #CodingInterviews #FibonacciRecursion #BigONotation #RecursionInDepth #Memoization #ExecutionTree #AlgorithmAnalysis #ComputerScienceBasics #LearnDSA #DataStructuresAndAlgorithms #CodeEfficiently #RecursiveFunctions #DSATutorial #TechWithCTO #CTOBHaiya #DSA2025 Your queries: time complexity recursion recursion time complexity recursion execution tree fibonacci recursion memoization recursion big o recursion recursive algorithms recursion explained recursion dsa coding interview recursion recursion vs memoization recursion time and space complexity dsa for beginners recursion for coding interviews recursion call tree recursive function complexity CHAPTERS 0:00 Introduction 0:33 Formula for calculating Time Complexity in Recursion 1:34 Factorial Example 2:40 Execution Tree for Recursion 4:21 Deriving 2^n Time for Fibonacci 7:01 Memoization Time Complexity 8:03 Conclusion =========================== ➡️ Connect with me: LinkedIn : https://www.linkedin.com/in/anuj-kumar-a-k-a-cto-bhaiya-on-youtube-9a188968 Telegram Channel : https://t.me/ctobhaiya_tg Instagram: https://www.instagram.com/ctobhaiya ===========================