Welcome to Part 2 of Code & Debug’s DSA Python Course 2025! 🎉 In this video, we’ll break down Time Complexity and Space Complexity, essential concepts for mastering Data Structures and Algorithms.
What you’ll learn in this lecture:
📌 The importance of time and space complexity in coding
📌 Big-O Notation explained step-by-step with Python examples
📌 Practical tips to write efficient and optimized code
👉 Refer the article below for better understanding of Time and Space Complexity:
https://codeanddebug.in/blog/time-com...
👉 📄 Access the full YouTube DSA Playlist Sheet (All Questions in Order):
🔗 https://docs.google.com/spreadsheets/...
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https://codeanddebug.in/course/master...
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https://codeanddebug.in/course/zero-t...
This session is ideal for coding interview preparation, competitive programming, or enhancing your problem-solving skills in Python.
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Timestamp:
0:00 Introduction to Time & Space Complexity
1:04 What is Time Complexity?
7:19 Big O Notation Explained
11:11 Rule 1 – Always Consider Worst Case
17:06 Rule 2 – Ignore Constants
19:00 Rule 3 – Ignore Lower Order Terms
20:58 Big O vs Omega vs Theta Notation
22:43 Example 1 – Nested Loops (O(n²))
26:04 Example 2 – Sum of Natural Numbers (O(n²))
30:50 What is Space Complexity?
36:03 Conclusion
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