Practical Data Structures & Algorithms for Software Engineering Interviews
Master essential data structures and algorithms, optimize problem-solving strategies, and ace technical interviews to become a top-tier software engineer.
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Introduction to DSA and Big O Notation
Unit 1: Foundations of DSA
Unit 2: Measuring Algorithm Efficiency
Unit 3: Practical Application of Big O
Arrays and Strings Fundamentals
Unit 1: Array Basics: The Building Block
Unit 2: String Essentials: Text as Data
Unit 3: Fundamental Array & String Algorithms
Advanced Array Techniques
Unit 1: Efficient Array Traversal
Unit 2: Sub-array and Sub-string Problems
Unit 3: Optimizing Range Queries
Unit 4: Array Manipulation & Analysis
Linked Lists: Singly and Doubly
Unit 1: Singly Linked Lists: The Basics
Unit 2: Doubly Linked Lists: Two-Way Street
Circular Linked Lists and Advanced Problems
Unit 1: Circular Linked Lists
Unit 2: Advanced Linked List Manipulations
Stacks: LIFO Data Structure
Unit 1: Stack Fundamentals
Unit 2: Stack Applications
Queues: FIFO Data Structure
Unit 1: Queue Fundamentals
Unit 2: Queue Implementations
Unit 3: Advanced Queue Types
Unit 4: Queue Applications
Hash Tables and Hash Maps
Unit 1: Hashing Fundamentals
Unit 2: Hash Functions and Collisions
Unit 3: Basic Hash Table Operations
Unit 4: Performance Analysis
Advanced Hashing Techniques
Unit 1: Collision Resolution Strategies
Unit 2: Optimizing Hash Table Performance
Unit 3: Hash Sets vs. Hash Maps
Unit 4: Practical Applications of Hashing
Introduction to Trees
Unit 1: Tree Fundamentals
Unit 2: Tree Traversal Techniques
Unit 3: Analyzing Tree Operations
Binary Search Trees (BSTs)
Unit 1: BST Fundamentals
Unit 2: Core BST Operations
Unit 3: BST Analysis and Applications
Balanced Binary Search Trees (AVL & Red-Black)
Unit 1: The Need for Balance
Unit 2: Introducing AVL Trees
Unit 3: Introducing Red-Black Trees
Unit 4: Comparing Balanced Trees
Heaps: Priority Queues
Unit 1: Heap Fundamentals
Unit 2: Core Heap Operations
Unit 3: Heaps as Priority Queues
Unit 4: Heap Applications
Tries (Prefix Trees)
Unit 1: Trie Fundamentals
Unit 2: Core Trie Operations
Unit 3: Trie Applications & Analysis
Graphs: Representation and Traversal
Unit 1: Graph Fundamentals
Unit 2: Representing Graphs
Unit 3: Graph Traversal Algorithms
Graph Algorithms: Shortest Paths
Unit 1: Introduction to Shortest Paths
Unit 2: Dijkstra's Algorithm
Unit 3: Bellman-Ford Algorithm
Unit 4: Comparing Shortest Path Algorithms
Graph Algorithms: Minimum Spanning Trees
Unit 1: Introduction to MSTs
Unit 2: Prim's Algorithm
Unit 3: Kruskal's Algorithm
Unit 4: Comparing MST Algorithms
Topological Sort and Cycle Detection
Unit 1: Introduction to Directed Acyclic Graphs
Unit 2: Topological Sorting Fundamentals
Unit 3: Implementing Topological Sort
Unit 4: Cycle Detection in Graphs
Unit 5: Applications of Topological Sort
Sorting Algorithms: Comparison-Based
Unit 1: Introduction to Comparison Sorts
Unit 2: Simple Sorting Algorithms
Unit 3: Comparing Simple Sorts
Sorting Algorithms: Efficient Comparison Sorts
Unit 1: Merge Sort: Divide and Conquer
Unit 2: Quick Sort: The Partitioning Powerhouse
Unit 3: Heap Sort: Leveraging Heaps
Unit 4: Comparing Efficient Sorts
Sorting Algorithms: Non-Comparison Based
Unit 1: Introduction to Non-Comparison Sorts
Unit 2: Counting Sort
Unit 3: Radix Sort
Unit 4: Bucket Sort
Unit 5: Summary and Comparison
Searching Algorithms
Unit 1: Introduction to Searching
Unit 2: Binary Search Fundamentals
Unit 3: Advanced Binary Search Applications
Recursion and Backtracking
Unit 1: Foundations of Recursion
Unit 2: Applying Recursion
Unit 3: Introduction to Backtracking
Unit 4: Advanced Backtracking Problems
Dynamic Programming: Introduction
Unit 1: DP Fundamentals
Unit 2: Memoization (Top-Down DP)
Unit 3: Tabulation (Bottom-Up DP)
Unit 4: DP Problem Solving
Dynamic Programming: Advanced Techniques
Unit 1: Tabulation: Bottom-Up DP
Unit 2: Identifying DP Problems & Optimization
Unit 3: Systematic DP Approach
Greedy Algorithms
Unit 1: Introduction to Greedy Thinking
Unit 2: Classic Greedy Problems
Unit 3: Advanced Greedy Applications
Unit 4: Proving Greedy Correctness
Divide and Conquer
Unit 1: Introduction to Divide & Conquer
Unit 2: Classic D&C Algorithms
Unit 3: Analyzing D&C Algorithms
Bit Manipulation
Unit 1: Foundations of Bitwise Operations
Unit 2: Practical Bitwise Applications
Unit 3: Advanced Bit Manipulation & Problems
Advanced Data Structures: Skip Lists & Bloom Filters
Unit 1: Skip Lists: Probabilistic Power
Unit 2: Bloom Filters: Probabilistic Membership
Problem Solving Strategies & Interview Preparation
