Sorting
Search
Hashing
Language detection
Dijkstra
Sorting
Search
Hashing
Language detection
Dijkstra
Complexity complexity complexity! Understanding time complexity in algorithms is the key for knowing and understanding the rest of it. Because the main clue behind it is how to write faster algorithms, faster means less time and better complexity.
If you understand that part very well you can start looking on the different sorting and searching algorithms.
Now after you learned about sorting and searching, you need to understand how to work with trees and graphs. Why is this important? How does it make you a better programmer? It is simple, just look on the structure of binary search tree for example and try to imagine you are dealing with a big set of data. Think about something like Google Maps, without Graphs and their algorithms (such shortest path) will be impossible to find the distance between two cities as fast as you see now.
Learning these things and skills will make you write efficient code and let you deal with complex and big data.
So
Complexity
Searching and sorting
Trees (specially binary search tree)
Graphs (specially shortest path algorithms)
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