### 1. Tree Traversal Algorithms

Trees are a linked-node data structure with a root node and sub-trees. These algorithms allow structured tree node visits.

### 2. Binary Search

When given a sorted array of elements and a search key, binary search works. It's a simple concept that's simple to grasp and put into practise.

### 3. Linear Search

It works by starting with the 0th element and comparing the user's input element to each term before returning the element's position.

### 4. Search Algorithms

This class of algorithms only has binary search. These algorithms underpin databases, virtual spaces, substructures, and quantum computers.

### 5. Sorting Algorithms

These algorithms arrange data to make meaning. Merge sort and quick sort are popular in this class.

### 6. Dynamic Programming

By storing previously calculated values and using them as needed, dynamic programming or memorization eliminates problems.

### 7. Quick Sort

Quicksort uses the last element as the pivot number, placing smaller numbers on the left and larger ones on the right.

### 8. Bubble Sort

It's a sorting algorithm that relates two adjacent elements and swaps them around until they're no longer in the right order.

### 9. Hashing Algorithms

Hash algorithms accept any data as input and use a hash table to generate a message that is consistent regardless of the data.

### 10. Graph Search Algorithms

Graphs, like trees, are non-linear data structures with nodes connected by edges. These work on trees, vertices-and-edges graphs, and any graph encoding.