Master Top Interviews with Data Structures and Algorithms

Boost your confidence and land your dream job with our comprehensive course on data structures and algorithms. Whether you're a student or a professional, this course is designed to help you succeed in top interviews and get the raise you deserve.

Our expert instructors will guide you through the key concepts and techniques that interviewers often ask about, including arrays & strings, linked lists & stacks, queues & trees, graphs & hashing, and sorting, searching & dynamic programming. You'll engage with practical exercises and real interview questions to ensure you're well-prepared for the toughest challenges.

But that's not all - our comprehensive practice test series features five carefully crafted tests, each containing a variety of questions that cover key DSA topics and real-world scenarios. With both multiple-choice questions (MCQ) and multiple-select questions (MSQ), you'll learn and understand the concepts behind each question, not just practice.

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