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@ -587,17 +587,17 @@ But don't forget to do coding problems from above while you learn!
- There are a lot of videos here. Just watch enough until you understand it. You can always come back and review.
- Don't worry if you don't understand all the math behind it.
- You just need to understand how to express the complexity of an algorithm in terms of Big-O.
- [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] [Skiena (video)](https://www.youtube.com/watch?v=z1mkCe3kVUA)
- [x] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
- [x] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [x] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] [Skiena (video)](https://www.youtube.com/watch?v=z1mkCe3kVUA) runing
- [ ] [UC Berkeley Big O (video)](https://archive.org/details/ucberkeley_webcast_VIS4YDpuP98)
- [ ] [Amortized Analysis (video)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] TopCoder (includes recurrence relations and master theorem):
- [x] TopCoder (includes recurrence relations and master theorem):
- [Computational Complexity: Section 1](https://www.topcoder.com/thrive/articles/Computational%20Complexity%20part%20one)
- [Computational Complexity: Section 2](https://www.topcoder.com/thrive/articles/Computational%20Complexity%20part%20two)
- [ ] [Cheat sheet](http://bigocheatsheet.com/)
- [ ] [[Review] Big-O notation in 5 minutes (video)](https://youtu.be/__vX2sjlpXU)
- [x] [Cheat sheet](http://bigocheatsheet.com/)
- [x] [[Review] Big-O notation in 5 minutes (video)](https://youtu.be/__vX2sjlpXU)
Well, that's about enough of that.
@ -607,8 +607,8 @@ if you can identify the runtime complexity of different algorithms. It's a super
## Data Structures
- ### Arrays
- [ ] About Arrays:
- [Arrays CS50 Harvard University](https://www.youtube.com/watch?v=tI_tIZFyKBw&t=3009s)
- [x] About Arrays:
- [Arrays CS50 Harvard University](https://www.youtube.com/watch?v=tI_tIZFyKBw&t=3009s)
- [Arrays (video)](https://www.coursera.org/lecture/data-structures/arrays-OsBSF)
- [UC Berkeley CS61B - Linear and Multi-Dim Arrays (video)](https://archive.org/details/ucberkeley_webcast_Wp8oiO_CZZE) (Start watching from 15m 32s)
- [Dynamic Arrays (video)](https://www.coursera.org/lecture/data-structures/dynamic-arrays-EwbnV)