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Phase 4

Core Algorithms

1

Time and Space Complexity: Big O Notation Explained

Learn how to analyze algorithm efficiency using Big O notation. Understand time complexity, space complexity, and how to evaluate the performance of your code.

18 mincomplexitybig-otime complexity
2

Data Structures: Arrays, Trees, Graphs, Hash Tables, and Their Trade-offs

Master essential data structures and understand when to use each one. Learn about arrays, linked lists, trees, graphs, and hash tables with their complexity trade-offs.

22 mindata structuresarraystrees
3

Sorting and Searching Algorithms: When to Use Which

Learn essential sorting and searching algorithms, their time complexities, and when to use each one. Compare quicksort, mergesort, heapsort, binary search, and more.

20 minsortingsearchingquicksort
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