Algorithms and Data Structures

This module covers the fundamental algorithms and data structures every software engineer should understand to write efficient, scalable code.

Sections

1. Big O Notation - Understanding algorithm complexity and scalability
2. Arrays and Objects Performance - Time and space complexity of fundamental data structures
3. Searching and Sorting - Common algorithms for finding and organizing data
4. Linked Lists, Stacks, and Queues - Fundamental linear data structures
5. Trees and Graphs - Hierarchical and network data structures
6. Recursion and Iterative Thinking - Approaches to solving problems
7. Dynamic Programming (Basics) - Optimizing recursive solutions
8. Problem Solving Patterns - Common algorithmic patterns and problem-solving strategies

Learning path

Start with Big O Notation to build the foundation for understanding why certain algorithms are better than others. Then proceed through the sections in order, as later topics build on earlier concepts.