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A Complete Roadmap To Learn Data Structures and Algorithms (DSA)

Last updated on Jan 10,2024 3.3K Views

Soumya Swain
Passionate about technology and its endless possibilities - driving innovation forward. Passionate about technology and its endless possibilities - driving innovation forward.

Introduction to Data Structures and Algorithms

Data Structures and Algorithms are two of the most important coding concepts you need to learn  if you want to build a bright career in Development. Majority of the top tech companies across the globe when hiring for Software Developers look for the candidate’s proficiency in Data Structures and Algorithms. In this article we will dive deep into the field of DSA using Java roadmap and explain how you can get started with DSA from Level 0. 

Topics to help you get started

  1. What are Data Structures and Algorithms?
  2. Market Trends: Increasing Demand for Software Developers
  3. Job security in Development Roles
  4. Can a non technical background person learn DSA using Java?
  5. Master a Programming Language: Java
  6. Benefits of learning Java
  7. Benefits of learning DSA using Java
  8. Important Data Structures to Learn
  9. Important Algorithms to Learn
  10. Get started with your DSA using Java journey

What are Data Structures and Algorithms? 

Data Structures is the process of storing, organizing, processing, and retrieving the data that is stored in the memory of the computer system so that it is easily accessible and used efficiently. The main agenda behind using data structures is to reduce the time and space complexities.

(Image: Types of Data Structures)

Algorithms are step-by-step instructions that are carried out to solve a problem or to complete an assigned task. Algorithms act like a roadmap used to complete a process.


Market Trends: Increasing demand for developers

Data structures and Algorithms (DSA) is one of the most valuable and sought-after skills when it comes to development roles. Companies are becoming widely data driven, which also requires them to adapt to new technologies, this in turn is giving rise to the need for developers worldwide.

Many companies like Amazon, Microsoft, Google, Apple and Meta recruit candidates who have excellent problem solving skills and have a strong understanding of data structures and algorithms (DSA). This is what helps the MAANG companies build high-performing softwares and applications.

According to the US Bureau of Labour Statistics Report the employment demand for developers will increase by 22% from 2020 to 2030 which is quite high compared to other sectors.

Peaking digital transformation demands skilled workers. 

 Job security in the field of development

Job security in development job roles is brilliant, especially for those with a strong skill set, specialized expertise, and commitment to continuous learning. As technologies continue to advance, the growing demand for developers is only set to increase 4x in the upcoming decade, in turn making development job roles a promising and stable career path.

Developer job roles have proven to be more resilient despite economic downturns. During the peak pandemic period, at an average, a software developer was able to get a salary hike of 120% with an average work experience of 2 years, which is uncommon in many fields. 

Can a person from non technical background learn Data Structures and Algorithms?

Yes, any person from a non-technical background can learn Data structures and Algorithms. It does not matter which educational background you belong to, all you need to have is a proper learning plan and willingness to learn.

Also one of the reasons why students fail to crack technical interviews is due to their lack of practical exposure and inability to approach an optimal solution when a problem statement is presented to them. In order to become a great coder, you need to be an excellent problem solver first, so build your DSA foundations and solve as many problems as you can. 

And there is a popular misconception that learning data structures and algorithms is good only for technical interviews but in reality, it is mainly about writing efficient code by minimizing time and space complexities.

Pro Tip: Think about the solution and the approach you want to take for good 5 to 10 minutes before looking into the Hint. Only search for the solution on the internet when you  really feel stuck and confused about the solution. 

How to get started with Data Structure and Algorithms? 

  • Learn a Programming Language
  • Learn the basics of Data Structures and types of Data Structures
  • Learn the basics of Algorithms and types of Algorithms
  • Learn Time and Space Complexities 
  • Practice multiple Problem Solving  approaches

Here is the Complete Data Structures and Algorithms (DSA) Roadmap for everyone who wants to learn all of it from Basics to Advanced level. 

Build a Strong Foundation in One Programming language

The very first step before learning Data Structures and Algorithms is to build a strong knowledge base on one programming language because the complete implementation of Data Structures and Algorithms depends on the programming language that you learn. You can start by learning any one programming language like Java, Python or C++. 

Over 90% of developers prefer Java programming language over C++  to implement  Data Structures. Python is a good programming language but it is not the most preferred language to learn DSA.

Learn Java

Java programming language was introduced in the year 1995 by Sun Microsystems & ever since its inception  it has been completely dominating the field of development. Thanks to Java’s  flexibility, scalability and versatility. It is also popular because of its WORA feature – Write Once Run Anywhere, that means you can write the code in Java and use it anywhere and run on any operating system.  

Benefits if Learning Java

  • Java is easy to learn
    Java is easy to learn as it follows the syntax that is similar to English. It was designed to compile,debug and write codes easily and efficiently when compared to other programming languages.
  • Java has a huge Open Source Libraries Support
    Java programming language being in the industry for decades has huge Open Source Library resources. Some of the resources such as Maven, JHipster, Apache Commons, Guava, Google-gson, Hibernate-ORM, Mockito etc., are available and can be used for making development in java easier.
  • Java has wide range of Development Tools
    Java language has the most important tools when it comes to development, it has  Integrated Development Environments (IDEs) that help in debugging, provide language support and much more. Some of the powerful development tools like Intellij, Eclipse, NetBeans etc are widely used across the globe by various developers.
  • Major Applications Run on Java
    There is no doubt Java is used everywhere. Today over 13 billion devices across the globe run Java. Tech giants like Microsoft, Google, Airbnb, Netflix, NASA use Java to build their applications. Java is also used in technologies such as Artificial Intelligence (AI), Blockchain and IOT (Internet of Things).
  • Huge Demand & Sky high pay for Java Developers
    With the popularity among various software and application developers rising, there is a huge ongoing demand for Java Developers. These java developers are paid high with the average entry-level salaries going up to 6-7 lakhs per annum.
  • Java gives you Competitive Advantage
    Java has its competitive advantage over other programming languages because of its acceptance and scope in software development, as it is quick in delivering solutions.

Benefits of learning DSA using Java

  • Helps you in becoming a Good Programmer.
  • Makes Codes more Scalable.
  • Enhance your Skills in solving complex problems more efficiently.
  • Explore more job opportunities in the development domain.
  • Crack interviews in Top Product based companies.

Important Data Structures to Learn

These are the most important concepts that help one in understanding data structures and algorithms in depth.

  • Arrays
    Arrays is a collection of data with similar data types and it is sequentially stored in the memory. It is a commonly used linear data structure hat is very easy to implement.
  • Linked Lists
    A Linked List is a linear data structure. Every linked list has two parts, the data section and the address section that holds the address of the next element in the list, which is called a node. Unlike Arrays, linked lists take perpetual time in adding and deleting any causal/inconsistent nodes.
  • Stacks
    Stacks are executed by Arrays or Linked lists. It follows a LIFO (Last In First Out) approach, which helps in determining backtracking, i.e., selecting elements in a specific order. It is commonly used to push, pop and peek.
  • Queues
    Queues follow FIFO (First-In-First-Out) Approach which is actually used when things are not required to be processed immediately, they are processed using FIFO Approach.
  • Graphs
    Graphs are non linear data structures with two main components – one being Vertices also known as Nodes and the other component is Edges also referred to as lines that link the Nodes (Vertices). Learning Graphs helps in describing different kinds of networks and solving problems.
  • Trees
    Trees are non-linear data structures similar to Graphs. Trees are clusters of Nodes and Edges that are connected in a hierarchical form. Unlike Linear data structure here the data is not structured on a linear basis.

Important Algorithms to Learn

  • Brute Force Algorithm
    The brute force algorithm is the simplest approach when it comes to finding a solution to a problem. The brute Force Algorithm provides all possible options that are available to solve a problem. The brute force algorithm is a feasible solution only when the input size is small, The efficiency of brute force reduces where the input size increases.
  • Recursive Algorithms
    Recursive Algorithm is a process where the problem is broken down into subsets and is called again and again until the problem is solved.
  • Searching Algorithms
    Search Algorithms is an algorithm that is used in following a step-by-step procedure to search and locate specific data among the data collected. The Search Algorithms are classified into two types sequential search and Interval search.
  • Sorting Algorithms
    A sorting Algorithm is an algorithm that is used to rearrange the list/data in a specific order such as highest value to lowest value or ascending order to descending order. Sorting helps in improving the efficiency of other algorithms. The output derived using the sorting algorithm should satisfy two conditions i.e., the output should be monotonic order or permutation of the input.
  • Hashing Algorithms
    Hashing algorithms are algorithms that are used to convert any kind of data to a unified message that generates output at a fixed length. All hash algorithms follow a mathematical, uniform, consistent, and one-way approach. Hashing algorithms are used majorly for file and document management, storing digital signatures and passwords.
  • Backtracking Algorithms
    Backtracking algorithms is an algorithm that uses the technique of brute force approach which finds all possible steps to solve a particular problem. During the process, it removes all those solutions which fail to solve the problem.
  • Greedy Algorithms
    A greedy algorithm is a problem-solving approach where, at each step, the algorithm chooses the locally optimal solution that seems best at that moment without considering the global picture or future consequences.
  • Dynamic Programming Algorithm
    Dynamic programming is a problem-solving technique wherein a complex problem is classified into smaller, more manageable subproblems, which are then solved recursively. This significantly reduces the computation time, as the solution to subproblems does not need to be determined or calculated again and again. The major reason to use dynamic programming is to store the solution to the problems and reuse it when required.

These are the most important concepts that help one in understanding data structures and algorithms in depth.



Data Structures and Algorithms are the building blocks for developing any kind of softwares and applications in today’s world. Learning Data Structures and Algorithms using Java helps one solve complex problems, code efficiently and crack interviews in top tech industries and enhances their problem solving skills.

How can you get started with Data Structures and Algorithms (DSA)?

You can start by attending a free Data Structures & Algorithms using Java demo session. Attending the session will provide you a clear insight into the field of DSA using Java, its importance and how students and working professionals can start their development journey from Level 0.


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A Complete Roadmap To Learn Data Structures and Algorithms (DSA)