By the end of this course, you will be able to:

✅ Understand essential data structures and algorithms
✅ Calculate the time and space complexity of a solution
✅ Convert problem statements into logical steps
✅ Develop brute-force and optimized approaches
✅ Recognize common problem-solving patterns
✅ Work confidently with arrays, strings, and matrices
✅ Implement essential searching and sorting algorithms
✅ Use hashing for faster lookup and frequency-based problems
✅ Solve problems using stacks and queues
✅ Create and manipulate linked lists
✅ Understand recursive thinking and the function call stack
✅ Apply bitwise operations to produce efficient solutions
✅ Identify and handle important edge cases
✅ Write clean, optimized, and interview-ready code
✅ Progress confidently to advanced DSA topics

Complete Course Curriculum

Module 1: Basic DSA

Build the foundation required to understand algorithms and approach coding problems correctly.

Topics Covered

• Introduction to Data Structures and Algorithms
• Importance and real-world applications of DSA
• Types of data structures
• Understanding algorithms
• Time complexity
• Space complexity
• Big O notation
• Best, average, and worst-case analysis
• Brute-force and optimized approaches
• How to understand a coding problem
• How to create a step-by-step solution
• Dry runs, test cases, and edge cases

Module outcome: You will understand how to analyze a problem and evaluate a solution before writing code.

Module 2: Basic Mathematics

Learn the mathematical techniques frequently used in coding problems and technical interviews.

Topics Covered

• Counting digits
• Extracting digits
• Reversing a number
• Palindrome numbers
• Armstrong numbers
• Factors and divisors
• Prime-number checking
• Greatest Common Divisor
• Least Common Multiple
• Modular arithmetic
• Sieve fundamentals
• Fast exponentiation
• Common number-based problems

Module outcome: You will be able to convert mathematical concepts into efficient programming logic.

Module 3: Arrays

Master one of the most important and frequently tested data structures.

Topics Covered

• Introduction to arrays
• Array creation and memory concepts
• Accessing and updating elements
• Array traversal
• Insertion and deletion
• Finding minimum and maximum values
• Reversing an array
• Rotating an array
• Prefix and suffix techniques
• Subarrays and subsequences
• Two-pointer technique
• Sliding-window technique
• Kadane’s algorithm
• Common array interview problems

Module outcome: You will recognize important array patterns and apply them to coding problems.

Module 4: Searching

Learn how to locate elements efficiently using basic and optimized searching algorithms.

Topics Covered

• Linear search
• Binary search
• Iterative and recursive binary search
• First and last occurrence
• Lower bound and upper bound
• Search insert position
• Searching in a rotated sorted array
• Finding peak elements
• Finding minimum in a rotated array
• Binary search on answers
• Comparing searching algorithms
• Searching interview problems

Module outcome: You will be able to select and implement the correct searching technique.

Module 5: Sorting

Understand how sorting algorithms work and when each technique should be used.

Topics Covered

• Introduction to sorting
• Bubble sort
• Selection sort
• Insertion sort
• Merge sort
• Quick sort
• Stable and unstable sorting
• In-place and out-of-place sorting
• Sorting custom data
• Comparing sorting algorithms
• Time and space complexity
• Sorting-based interview problems

Module outcome: You will understand how different sorting algorithms organize data and how their performance differs.

Module 6: Strings

Learn how to process, compare, search, and transform textual data.

Topics Covered

• Introduction to strings
• String creation and traversal
• Character operations
• Comparing strings
• Reversing strings and words
• Palindrome checking
• Character-frequency counting
• Removing duplicate characters
• Anagrams
• Substrings and subsequences
• String pattern problems
• Common string interview questions

Module outcome: You will be able to solve frequently asked string problems using structured approaches.

Module 7: Hashing

Use hash-based data structures to perform faster searching, counting, and lookup operations.

Topics Covered

• Introduction to hashing
• Hash functions
• Hash sets
• Hash maps
• Frequency counting
• Finding duplicate elements
• Pair-sum problems
• Character and word frequencies
• Understanding hash collisions
• Time-complexity analysis
• Common hashing patterns
• Interview problems based on hashing

Module outcome: You will know when hashing can replace repeated scanning with faster data access.

Module 8: Stack

Understand the Last-In, First-Out data structure and its most important applications.

Topics Covered

• Stack fundamentals
• Push, pop, peek, and isEmpty
• Array-based stack implementation
• Linked-list stack implementation
• Balanced parentheses
• Expression evaluation
• Infix, prefix, and postfix expressions
• Next greater element
• Next smaller element
• Monotonic stack fundamentals
• Stack-based interview problems

Module outcome: You will recognize problems that can be simplified using stack operations.

Module 9: Queue

Learn how First-In, First-Out processing is used in algorithms and real-world applications.

Topics Covered

• Queue fundamentals
• Enqueue, dequeue, front, and rear
• Array-based queue implementation
• Linked-list queue implementation
• Circular queue
• Double-ended queue
• Priority queue fundamentals
• Implementing a queue using stacks
• Implementing a stack using queues
• Queue-based interview problems

Module outcome: You will understand how queues manage ordered processing efficiently.

Module 10: Linked List

Learn how nodes and references are used to create dynamic data structures.

Topics Covered

• Introduction to linked lists
• Nodes and references
• Singly linked lists
• Doubly linked lists
• Circular linked lists
• Insertion and deletion
• Linked-list traversal
• Reversing a linked list
• Finding the middle node
• Detecting a cycle
• Removing a cycle
• Merging linked lists
• Common linked-list interview problems

Module outcome: You will be able to create, modify, traverse, and solve problems involving linked lists.

Module 11: Matrix

Develop the skills required to process and manipulate two-dimensional data.

Topics Covered

• Introduction to two-dimensional arrays
• Matrix input and output
• Row-wise traversal
• Column-wise traversal
• Diagonal traversal
• Boundary traversal
• Matrix transpose
• Matrix rotation
• Spiral traversal
• Searching in a sorted matrix
• Matrix transformations
• Common matrix interview problems

Module outcome: You will be able to solve two-dimensional data problems using efficient traversal techniques.

Module 12: Recursion

Learn how complex problems can be solved by dividing them into smaller versions of the same problem.

Topics Covered

• Introduction to recursion
• Base case and recursive case
• Understanding the recursion call stack
• Tracing recursive functions
• Factorial using recursion
• Fibonacci using recursion
• Recursive array problems
• Recursive string problems
• Generating subsequences
• Introduction to backtracking
• Recursion versus iteration
• Time and space complexity of recursion

Module outcome: You will understand recursive execution and develop correct recursive solutions.

Module 13: Bit Manipulation

Learn how binary and bitwise operations can produce compact and efficient solutions.

Topics Covered

• Binary-number fundamentals
• Bitwise AND
• Bitwise OR
• Bitwise XOR
• Bitwise NOT
• Left-shift and right-shift operators
• Checking a bit
• Setting and clearing a bit
• Toggling a bit
• Checking odd and even numbers
• Checking powers of two
• Counting set bits
• Finding unique elements using XOR
• Common bit-manipulation problems

Module outcome: You will be able to apply bitwise operations to solve problems efficiently.

Who Should Join This Course?

This course is ideal for:

• Beginners starting their DSA journey
• College students preparing for placements
• Freshers preparing for technical interviews
• Students preparing for coding assessments
• Learners who know programming syntax but struggle to solve problems
• Self-taught programmers looking for a structured roadmap
• Developers who want to strengthen their fundamentals
• Anyone planning to learn advanced DSA

Who Should Join This Course?

This course is ideal for:

• Beginners starting their DSA journey
• College students preparing for placements
• Freshers preparing for technical interviews
• Students preparing for coding assessments
• Learners who know programming syntax but struggle to solve problems
• Self-taught programmers looking for a structured roadmap
• Developers who want to strengthen their fundamentals
• Anyone planning to learn advanced DSA

Prerequisites

No previous knowledge of Data Structures and Algorithms is required.

A basic understanding of the following programming concepts will be helpful:

• Variables and data types
• Conditional statements
• Loops
• Functions
• Basic input and output

Your Transformation

Earn Your Course-Completion Certificate

Complete the Basic DSA course and receive an ExamAdda certificate recognizing your learning and commitment.

You can add your certificate to:

• Your résumé
• LinkedIn profile
• College portfolio
• Internship applications
• Job applications

What Can You Learn Next?

After completing Basic DSA, you will be prepared to study:

• Trees
• Binary Search Trees
• AVL Trees
• Heaps and Priority Queues
• Greedy Algorithms
• Backtracking
• Graphs
• Dynamic Programming
• Tries
• Disjoint Set Union
• Segment Trees
• Advanced problem-solving patterns