Data Structure and Algorithms Tutorial PDF Free Download | Online DSA Tutorial for Beginners & Professionals

Learning data structures and algorithms gives us proper knowledge to write efficient and optimized computer programs. Basically, a computer program is a set of instructions provided to execute a particular task. To achieve this, a computer program requires to store and retrieve data and run computations on the data. BTech Geeks Data Structure and Algorithms Tutorial will give proper guidance in learning various types of DSA and their implementations in C, C++, Java, and Python.

What is Data Structure and Algorithms?

The named location that stores and organize data is known as Data structure. And, the group of steps to solve a specific problem is called an Algorithm. Our DSA Tutorial will provide you an excellent Data Structures knowledge required to learn the complexity of enterprise-level applications and the knowledge about algorithms for taking a set of inputs needed and provides the desired output at the end.

Do Check:

List of Topics Covered in DSA Tutorial PDF

This DSA Free Online Beginners Guide will provide basic and advanced concepts of Data Structure and Algorithms like listed below. So, take a look at the available links and learn core concepts of data structure & algorithms.

  • Create a Binary Search Tree from an array
  • Remove Duplicate Elements from a Sorted Singly Linked List
  • Reverse a Singly Linked List in a Single Iteration
  • Create a Singly Linked List from an array
  • Finding paths in a Binary Tree
  • Finding nth Largest and Smallest Node in Binary Seach Tree
  • Converting a Binary Search Tree to a Sorted Doubly Linked List
  • Designing a Binary Search Tree Validation class
  • Binary Tree Traversal with Strategy design pattern and open-closed principle

Prerequisites for learning DSA

Want to learn data structures and algorithms efficiently? then check out the prerequisites that you need to know. Here is the list as follows:

  • Need to have the basics of the core C language that aid you gain many insights into a data structure.
  • Should spend a bit of time in programming in C++, Java, and Python.
  • Moreover, for DSA programming learnings you must have knowledge of fundamental concepts such as loops, inheritance, polymorphism, arrays, strings, memory allocation, and pointer.
  • Also, elementary mathematics knowledge and reasoning helps you understand concepts even efficiently.

What is an Algorithm?

An algorithm is a confined collection of instructions or logic written in a specific order to achieve a particular task.
Moreover, it is a core logic of a problem that is declared as an unofficial high-level report as pseudocode or using a flowchart.

One of the most useful advantages of Algorithms is to rush up the execution process and diminish the memory requirement. The algorithm performance measured based on two main properties. They are as such, Time Complexity and Space Complexity. 

The properties that should be satisfied by every algorithm are listed below:

  • Input: There must be 0 or more inputs provided externally to the algorithm.
  • Output: There should be a minimum of 1 output achieved.
  • Definiteness: Each step in the algorithm must be clear and unambiguous.
  • Finiteness: The algorithm needs to have a limited number of steps.
  • Correctness: Each step of the algorithm required to generate the correct output.

Features of Good Algorithms

Some of the algorithm features are mentioned here for a better understanding of the concepts:

  • Input and output need to define precisely.
  • Algorithms should be the most effective amid numerous different ways to solve a problem.
  • It doesn’t involve any kind of computer code.
  • Rather, the algorithm ought composed in such a way that it can be utilized in various programming languages.

Basic Types of Data Structures (DS)

Basically, there are two types of data structures. One is a Primitive data structure and the second one is a Non-primitive data structure.

Primitive Data structure: The primitive data types are known as primitive data structures such as int, char, float, double, and pointer which exist a single value.

Non-Primitive Data structure: This type of DS is classified into two types and are a Linear data structure and Non-linear data structure.

Why Learn Data Structure and Algorithms?

An input, Process, and Output are the three main steps of the basic program. In order to make the execution of the program fast and efficient, optimization is needed. For this, the Data structure and algorithms dive in. It does data storage in a structured format that’s the reason to process and displayed easily.

Besides, Algorithms support reducing memory space and processing data quickly. Whenever the program complexity rises, DSA becomes very important in enhancing the performance of the program.

Also, there are some common issues that applications are facing nowadays like Data Search, Processor speed, and Multiple requests. For overcoming these issues, we have to learn Data structures and algorithms as they come to protect.

Data structures and Algorithms Interview Questions List

The following questions have appeared in various software job interviews related to Data structures and algorithms. So, have a glance at the Interview Questions of DSA Programming and crack your interview rounds.

  1. What is data structure?
  2. What is an algorithm?
  3. What is binary search?
  4. Briefly explain the approaches to develop algorithms.
  5. Give some examples of greedy algorithms.
  6. How breadth first traversal works?
  7. How depth first traversal works?
  8. How insertion sort and selection sorts are different?
  9. How quick sort works?
  10. Tell me something about ‘insertion sort’?
  11. What are asymptotic notations?
  12. What are common operations that can be performed on a data structure?
  13. What are some examples of divide and conquer algorithms?
  14. What are some examples of dynamic programming algorithms?
  15. What are the criteria of algorithm analysis?
  16. What are various data structures available?
  17. What is a binary search tree?
  18. What is a binary tree?
  19. What is a graph?
  20. What is a linked list?
  21. What is a queue in data structure?
  22. What is a tree?
  23. What is an asymptotic analysis of an algorithm?
  24. What is bubble sort and how bubble sort works?
  25. What is linear data structure?
  26. What is linear searching?
  27. What is merge sort and how it works?
  28. What is selection sort?
  29. What is shell sort?
  30. What is a stack?
  31. What is tree traversal?
  32. What operations can be performed on Queues?
  33. What operations can be performed on stacks?
  34. Why do we use queues?
  35. Why do we use stacks?