Course Description

This course is designed for individuals who already possess basic programming skills—whether self-taught or through previous study (for instance, completing our Web course). You’ll learn a systematic approach to algorithmic patterns and data structures, covering everything from Two Pointers and Binary Search to DFS/BFS, Sliding Window, Heaps/Hashing, Merge Patterns, Backtracking & Subsets, Dynamic Programming, Tries, and Topological Sort. By the end, you’ll be ready to tackle high-level coding interviews and real-world optimization challenges.

What You Will Learn

• Data Structures
  • Arrays & Linked Lists
  • Stacks & Queues
  • Hash Maps & Sets
  • Heaps (Min/Max)
  • Tries (Prefix Trees)
  • Select Custom Structures (e.g., LRU Cache)
• Algorithmic Patterns
  • Two Pointers (including Fast & Slow)
  • Binary Search (efficient lookups in sorted data)
  • DFS & BFS (Trees, Graphs, plus Matrix BFS)
  • Sliding Window (optimizing subarray/string scenarios)
  • Heaps & Hashing (priority queues, frequency counting)
  • Merge Patterns: Merge Intervals, K-way Merge
  • Backtracking & Subsets (constraint-based search, permutations)
  • Dynamic Programming (knapsack, coin change, partition, etc.)
  • Topological Sort (dependency management in DAGs)

Overall Information

• Prerequisites: A solid grasp of at least one programming language (e.g., Python, Java, C++, JavaScript)
• If you have completed our Web course, you already have the foundational coding skills needed
• Focuses on step-by-step mastery of patterns, data structures, and problem-solving workflows
• Ideal for coding interview preparation and practical development scenarios

Target Audience

• Programmers & Developers looking to expand their algorithmic toolkit
• Interview Candidates aiming to confidently handle a variety of problem types
• CS Enthusiasts eager to learn advanced concepts