Data Structures & Algorithms: Building Blocks of Efficient Code 🧱⚙️

What Are Data Structures & Algorithms?

Data structures are organized ways to store and manage data efficiently. Algorithms are step-by-step procedures to solve problems. Together, they form the foundation of computer science! 🚀

Key Concepts

• Data Structures: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Hash Tables, etc.
• Algorithms: Sorting, Searching, Recursion, Dynamic Programming, Greedy Algorithms, etc.
• Time & Space Complexity: Measure efficiency using Big O notation. ⏱️💾

Popular Data Structures

1. Array 📊

   • Stores elements in contiguous memory locations.
   • Example: [1, 2, 3, 4]
   

2. Stack 📦

   • LIFO (Last In, First Out) principle.
   • Used in function calls, undo mechanisms.
   

3. Queue 🚶

   • FIFO (First In, First Out) principle.
   • Applied in task scheduling, breadth-first search.
   

4. Binary Tree 🌳

   • Hierarchical structure with nodes and children.
   • Essential for searching and sorting operations.
   

Algorithm Categories

• Sorting: Bubble Sort, Merge Sort, Quick Sort.
• Searching: Linear Search, Binary Search.
• Graph Algorithms: Dijkstra's, BFS, DFS.
• Dynamic Programming: Fibonacci, Knapsack.
• Greedy Algorithms: Huffman Coding, Prim's Algorithm.

Learn More

• Dive deeper into data-structures-algorithms tutorials
• Practice coding challenges at data-structures-algorithms/exercises
• Explore data-structures-algorithms/visualizations for interactive examples

Fun Facts

• 🧠 The concept of algorithms dates back over 2000 years to ancient Greece!
• 💻 Data structures and algorithms are critical for optimizing code performance.
• 📚 Mastering them can unlock advanced topics like machine learning and system design!

For a visual guide to binary_search, click the link!