Mastering data structures and algorithms takes time and consistent effort. Every company definitely asked DSA questions for various engineering profiles in interview. It is one of the most essential skill required for every software engineer out there. We will be going from the steps to learn DSA in very efficient way.
Pick a Programming Language
To practice one must choose the language and learn all the basic concepts of that programming language. Most people use C++, Java, and Python as they are easy and clear the fundamentals easily. Programming language doesn’t matter. You can choose any language you are comfortable with.
Learn the basic concepts of language like conditional statements, loops, variables, functions, recursion, etc.
Learn the fundamentals of Data Structures
To master DSA learning the basics and understanding the core concepts are more important. As we move further in the DSA journey, we always reach to the point where the code doesn’t work. So, in such situations, fundaments come into the picture to solve complex problems.
Basically, there are two types of Data structures Linear and Non-Linear Data Structures.
Linear Data Structures
Array
Arrays are nothing but the group/collection of similar data types like integers, floats, doubles, strings, etc. Elements in the array are accessed by their index and the index starts from 0. Arrays are used to store data temporarily. We can perform various operations on an array like insertion, traversal, deletion, searching, updation, etc.
Linked List
Linked List stores data in a sequential order. Every node is connected to its adjacent nodes. Each node stores the data and the address of the next/previous node. There are various types of linked list namely as Singly Linked List, Doubly Linked list, and Circular Linked list.
Stack
A stack data structure stores the data on top of each other’s elements. It processes the mechanism LIFO (Last In First Out). We can perform several operations like push and pop to add and remove elements respectively. It is used in the browser to go to the previous and next page. The stack can be implemented by using arrays and linked lists.
Queue
Queue stores data in an order and follows the FIFO (First In, First Out) principle. There are various types of queues circular queue, priority queue, and double-ended queue. Queues are mainly used in task scheduling and serving HTTP requests to servers.
Non-Linear Data Structures
Trees
It is a hierarchical data structure used to store data. There are various types of trees Binary Trees, Binary Search Trees, AVL Trees, etc. Various operations can be performed on trees like searching, traversing, sorting, deletion, etc.
Graphs
Graphs consist of nodes and edges. Each node can connect with n nodes with n edges. Graphs are highly used to manage social networks to track followers and following. Google Maps uses graphs to store geological data.
Learn Algorithms
Algorithms are very important when it comes to solving complex problems. Now, what does algorithm mean? It is a step-by-step process or instructor to solve problems.
Based on the problem we must pick the correct algorithms to solve it easily. Here are some algorithms available –
Sorting Algorithms
- Bubble Sort
- Merge Sort
- Quick Sort
- Insertion Sort
- Bucket Sort
- Selection Sort
Searching Algorithms
- Linear Search
- Binary Search
Greedy Algorithms
Greedy algorithms are mainly used when we have to find the best optimal solution. So, on each step this algorithm finds the best possible optimal choice.
Backtracking
Backtracing explores all possible ways to solve the given problems. It backtracks the step whenever it is required. It is the same as recursion but with additional steps.
Complexity Analysis
Every problem we solve on the computer requires some time and space. Optimizing problems to use resources is very crucial. Hence, there are two types of complexity analysis we perform, every time when we solve any given problem.
- Time Complexity – It measures the time taken to solve the problem
- Space Complexity – It measures the space used by a given solution.
Platforms to practice DSA
DSA required consistency. To master DSA we have to learn and solve problems every single day. There are various platforms available to practice.
Maintain a streak and solve at least one problem every day. Don’t look for hints and solutions. If any problem takes more time, then think about it, write it down on paper, and solve step by step. Divide the problem into smaller steps to solve it efficiently.
Mastering DSA is not a one-night process. It requires consistent efforts and learning in the right direction
Also read, Will AI Replace Programmers In Future? Learn These Technologies ASAP
