This course is designed for students and professionals who want to land a job or get a raise by successfully passing top interviews that focus on data structures and algorithms.

In this course, you will learn the important concepts and techniques that interviewers often ask about. Whether you’re new to programming or have some experience, this course will help you strengthen your skills and boost your confidence.

You’ll engage with practical exercises and real interview questions to ensure you’re well-prepared.

In this comprehensive practice test series, you'll engage with five carefully crafted tests, each containing a variety of questions that cover key DSA topics and real-world scenarios. Our tests feature both multiple-choice questions (MCQ) and multiple-select questions (MSQ), with detailed explanations provided for every answer. This means you won’t just practice - you’ll learn and understand the concepts behind each question.

Course Outline:

1. Arrays & Strings

   • Array Basics

   • Two-Pointer Technique

   • Sliding Window

   • String Manipulation

   • Common Array Problems (e.g., Maximum Subarray, Rotate Array)

   • Common String Problems (e.g., Anagrams, Palindromes)

2. Linked Lists & Stacks

   • Linked List Fundamentals

   • Single vs. Doubly Linked Lists

   • Stack Operations

   • Applications of Stacks (e.g., Expression Evaluation)

   • Common Linked List Problems (e.g., Reversal, Cycle Detection)

   • Stack Problems (e.g., Valid Parentheses, Next Greater Element)

3. Queues & Trees

   • Queue Fundamentals

   • Circular Queue and Priority Queue

   • Tree Basics (Binary Trees, Binary Search Trees)

   • Tree Traversals (Inorder, Preorder, Postorder)

   • Common Tree Problems (e.g., Lowest Common Ancestor, Depth Calculation)

4. Graphs & Hashing

   • Graph Representation (Adjacency List, Matrix)

   • Graph Traversal Algorithms (BFS, DFS)

   • Shortest Path Algorithms (Dijkstra’s, Bellman-Ford)

   • Hash Table Basics

   • Common Hashing Problems (e.g., Two Sum, Anagrams)

5. Sorting, Searching & Dynamic Programming

   • Sorting Algorithms (Quick Sort, Merge Sort, Bubble Sort)

   • Search Algorithms (Binary Search, Linear Search)

   • Basics of Dynamic Programming

   • Common DP Problems (e.g., Fibonacci, Knapsack Problem)

   • Recursion vs. Iteration