# How to learn algorithms and data structures to be a professional developer.

## How to learn algorithms and data structures to develop new skills?

If you want to learn algorithms and data structures to build your skills. then you are in right place. to fully understand how to learn algorithms and data structures full read this post. then you guess that this is right for you or not.
so let's start the topic...

### How to learn Algorithms:

If you are a technical person then you should know what is algorithms. and if you don't know then I will tell you.
the algorithm is a way to solve the problem. and used for creating logics and get the best and simple solution to the problem. and used for getting effective method for a problem. and it has a starting point and ending point.

now the technology becomes wide. and every day we face new problems in the technical field. so the algorithm is the best way to solve any problem and get the idea that how a problem solve. and in now time this thing is essential and recommended. algorithms

#### "so there are the lists of topics which you should learn in algorithms for solving any type of technical problem."

first of all, you need to know what is algorithms and why we used this topic to solve the problem.
then you should get started in the field of algorithms.

First step.
Learn these topics:
1. How to sort an algorithm. like how to combined two conditions in one condition.
2. Should learn how to analyzing and designing algorithm.

Second step.
Learn these topics:
1. what is big O notation.
2. what is Asymptotic notation.
3. what is Standard notation.

Third step.
Learn these topics:
1. The indicator of random variables and random algorithm.
2. The hiring problem.
3. Probabilistic analysis.

Fourth step.Learn these topics:
1. Bellman-Ford algorithm.
3. Dijkstra's algorithm.
4. The simplex algorithm.
5. Relabel-to-front algorithm.
6. Johnson's algorithm.
7. Floyd-Warshall algorithm.
8. Kruskal and Prim algorithm.
9. Push-relabel algorithm.
10. Knuth-Morris-Pratt algorithm.
11. Strassen's algorithms.

for the better understanding of algorithm and for practice. you can solve these problems. like Rotations, insertion, deletion, matrix multiplications, recursion, hiring problem.

and you should be used algorithms to solve the data structure problems. like how to create link list.
and how to create stacks and queues.

how to represent trees and creating binary trees.
problems for Hashtables.
for creating Heaps.

### How to learn Data Structures:

Further learning Data Structures you have at least knowledge of one programming language. so you can easily and fully understand this topic.

Data structure uses to arrange to data. because in now time the production of data on the internet grow up rapidly. and all the data is in unstructured form. data structures

Data structures included many topics. and to be professional and to solve any problem it's recommended first.

It includes:

1. Pointers and Arrays
3. Stacks.
4. Queues.
5.  Searching and Sorting Algorithms.
6. Hashing algorithms.
7. Binary tree.
8. Graphs.
9. Standard template library.

Step First:
1. Dynamic variables.
4. Pointer-based operations.
5. Dynamic arrays.
6. Shallow and Deep copy.
7. time complexity.
8. polynomial operations.

Step Second:
2. Item insertion and deletion in the link list.
3. Structures of linked list nodes.
4. Node type member variables.
6. Destroy the list.
7. Initialize the list.
8. Print the list.
9. Length of a list.
10. Retrieve the data of the first node and last node.
11. Begin and end of the list.
12. Copy the list.

Step third:
1. Initialize stack
2. Empty and full stack.
3. Push and Pop operations.
4. Copy stack.
5. Implement a stack as an array.
7. postfix, prefix, and infix expression.

Step fourth:
1. Initialize queue.
3. Empty and full queue.
4. Front and back queue.
5. Designing a queuing system.
6. single queue.
7. circular queue.

Step fifth:
Learn about the searching and sorting algorithms:
1. Sequential search/linear search.
2. Binary search.
3. Bubble sort.
4. Sorting by: bubble sort.
5. Insertion sort.
6. selection sort.
7. quicksort.
8.  heap sort.
9.  merge sort.
11. counting sort.

Step six:
1. Hash-table.
2. Hash function.
3. Collision resolution.
4. Open addressing using the hash.
6. Chaining.

Step Seven:
1. Trees.
2. Properties of the trees.
3. Binary Tree
4. Operations on a Binary Tree.
5. Representation of Binary trees using arrays and linked lists.
6. Traversing on a binary tree.
7. Binary search tree.
8. B-tree.
9. B+ tree.
10. AVL tree.

Step Eight:
1. Basic concepts of graphs.
2. Different representations of Graphs.
3. Breath first search.
4. Depth-first search.
5. Minimum Spanning Tree.
6. Prim's algorithms.
7. Kruskal algorithms.
8. Dijkstra's algorithms.

these are all topics are the foundation of data structures. just learn these topics.

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