Code Speed Secrets: Big O Explained! 🚀 #coding #dsa
April 03, 2025Video Details
- Style
- Realistic
- Genre
- General
- Voice
- Amy
- Language
- English
Creative Input
Prompt
Create a video for a challane 100 days of DSA day 1 showing a student studying on computer
Script
🎬 **Opening Hook (First 3 seconds)**: "Ever wondered why some codes run fast while others take forever? It's all about *Time Complexity!* Let’s break it down!" 📌 **Main Content (15-30 sec):** "Time complexity tells us how fast an algorithm runs as the input grows. We use **Big O notation** to express it. Here’s a quick breakdown: 🔹 **O(1)** - Constant time, like accessing an array element. 🔹 **O(N)** - Linear time, like iterating a list. 🔹 **O(N²)** - Quadratic time, like nested loops. 🔹 **O(2^N)** - Exponential time, common in recursion-heavy problems. The lower the complexity, the better the performance!" 📌 **Ending CTA (Call to Action, 5 sec):** "Follow for more DSA breakdowns! 💡 Drop a 🔥 if you got this!"