Learn Data Structures and Algorithms in Python

1. Algorithms Intro
   Learn about what algorithms are and why they matter
2. Math
   Learn the math required to understand Big-O notation, namely exponents, logarithms, and factorials
3. Big-O Analysis
   Figure out what Big-O notation and time complexity mean in the context of algorithms and performant code
4. Sorting Algorithms
   Learn how data is sorted on a computer, and how to sort it faster
5. Exponential Time
   Understand why exponential time complexity is so dangerous
6. Data Structures Intro
   Learn about data structures and how they play a critical role in algorithms
7. Stacks
   Learn about stacks, the original LIFO data structure and build one from scratch
8. Queues
   Learn about the FIFO queue data structure and how to implement a simple one from scratch
9. Linked Lists
   Understand how linked lists vary from arrays and how to use one to build a faster queue
10. Binary Trees
    Learn about binary trees, what they are used for, and implement one from scratch
11. Red Black Trees
    Solve the classic balancing problem of traditional binary trees with a red-black algorithm
12. Hashmaps
    Build a hashmap from scratch and learn how to use the Python dictionary type effectively
13. Tries
    Build all the methods of a trie class, and efficiently search entire documents of text
14. Graphs
    Learn about graph structures and how we can use them to quickly solve a wide array of search problems
15. BFS and DFS
    Implement and understand the ever-famous breadth first and depth-first search algorithms
16. P vs NP
    Learn about P and NP

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