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@@ -15,16 +15,15 @@ I highly recommend the following materials by the ordered by importance:
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- [Youtube playlist](https://www.youtube.com/watch?v=0IAPZzGSbME&list=PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O) [If you are a begineer]
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- [CLRS book](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844) [If you are an academic].
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TLDR Objectives: Understanding of various types of techniques for algorithms
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design and (run time) analysis in detail. Also, a gentle introduction to several
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advanced data structures.
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TLDR Overview: Review of mathematical background, sorting and searching,
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algorithm design techniques such as divide and conquer, greedy approach, dynamic
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programming, worst case and average case analysis techniques, data structures
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such as binary search trees and various heaps, graph algorithms, string
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algorithms and geometric data structures, advanced topics (P, NP, NP-Complete,
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etc) if time permits.
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Practice the following:
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- [Problem sets from textbook](https://www.amazon.com/Data-Structure-Algorithmic-Thinking-Python/dp/8192107590)
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- [Online programming](https://leetcode.com/)
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My personal experience stems from taking PhD courses at UCF:
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[Udacity nano degree: Data Structures and
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Algorithms](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256)
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[COT 5405: Design & Analysis Algorithms](http://www.cs.ucf.edu/~sharma/COT5405)
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[COT 6410: Computational Complexity](http://www.cs.ucf.edu/courses/cot6410/Spring2021/COT6410Spring2021.html)
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Solving any algorithm problem:
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==============================

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