How to Learn Algorithms & Data Structures | DSA Tutorials

Guide on How to Learn Algorithms and Data Structures – An algorithm is a well-defined list of different steps for solving a particular problem. Let’s say if you want to make a coffee, then the list of steps you are going to follow to make a coffee is the algorithm of coffee. On the other side a data may be organized in many different ways – the logical or mathematical model organisation of data is called data structures.

But to solve a particular problem, we can have multiple algorithms and can use different types of data structures to store the data. To choose the best algorithm and data structure for your problem set, we need to understand/learn about Data Structures and Algorithms.

How to learn algorithms?

The algorithm is a way to solve the problem. and used for creating logic and getting the best and simplest solution to the problem. and used to find an effective method for a problem. and it has a starting point and an ending point. 

Now the technology is becoming widespread. 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 of how a problem is solved. And now time this thing is essential and recommended.

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 algorithms are and why we use them to solve the problem. Then you should get started in the field of algorithms. Below is a step-by-step process to learn the algorithm. Follow and learn all these topics, and you will be a master in algorithms and data structures.

First step

1. How to sort an algorithm
2. Should learn how to analyse and design an algorithm

Second step

1. What is big O notation
2. Big O notation examples
3. What is Asymptotic notation
4. What is Standard notation

Third step

1. The indicator of random variables and a random algorithm
2. The hiring problem
3. Probabilistic analysis

Fourth step

1. Bellman-Ford algorithm
2. Multithreaded algorithms
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 a better understanding of the 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 a linked list. 

And how to create stacks and queues. How to represent trees and create 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. A data structure is used to arrange data. Now, the time for the production of data on the internet is growing rapidly. And all the data is in unstructured form.

Data structures included many topics. and to be professional and to solve any problem, it’s recommended first. The included topics are –

1. Pointers and Arrays
2. Linked lists
3. Stacks
4. Queues
5. Operations on Linked list
6. Searching and Sorting Algorithms
7. Hashing algorithms
8. Binary tree
9. Graphs
10. Standard template library

Learn about Arrays

1. Dynamic variables
2. About the new operator
3. About delete operator
4. Pointer-based operations
5. Dynamic arrays
6. Shallow and Deep copy
7. Time complexity
8. Polynomial operations

Learn about the Linked list

1. Building a linked list
2. Item insertion and deletion in the link list
3. Structures of linked list nodes
4. Node type member variables
5. Linked list iterators
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
13. Header-linked list
14. Merge two linked lists
15. Single-linked list
16. Doubly linked list
17. Circular linked list
18. Insertion in Circular linked list
19. Ordered linked list
20. Unordered linked list

Learn about Stacks

1. Initialize stack
2. Empty and full stack
3. Push and Pop operations
4. Copy stack
5. Implement a stack as an array
6. Stack header file
7. Postfix, Prefix, and Infix expressions

Learn about the queues

1. Initialize queue
2. Add and delete queue
3. Empty and full queue
4. Front and back queue
5. Designing a queuing system
6. Single queue
7. Circular queue
8. Dequeue
9. Priority Queue

Learn about the searching and sorting algorithms

1. Sequential search/linear search.
2. Binary search
3. Bubble sort
4. Bubble sort
5. Insertion sort
6. Selection sort
7. Quicksort
8. Heap sort
9. Merge sort
10. Radix sort
11. Counting sort

Learn about the Hash algorithms

1. Hash-table
2. Hash function
3. Collision resolution
4. Open addressing using the hash
5. Hashing using quadratic probing
6. Chaining

Learn about the tree

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
11. Threaded binary tree

Learn about the Graph

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

All these topics are the foundation of data structures. Just learn these topics.