Welcome to Module 3 of our documentation! This guide dives into advanced algorithms that are essential for optimizing performance and solving complex problems. Let's explore key topics together! 🚀

🔑 Key Concepts Covered

  • Time Complexity Analysis ⏱️
    Understand how to evaluate algorithm efficiency using Big O notation.

    Time_Complexity

  • Graph Theory Algorithms 🌐
    Learn about Dijkstra's algorithm, Kruskal's algorithm, and more.

    Graph_Theory

  • Dynamic Programming 🧩
    Master techniques for breaking down problems into overlapping subproblems.

    Dynamic_Programming

  • Advanced Data Structures 📂
    Explore heaps, balanced trees, and hash tables for efficient operations.

    Advanced_Data_Structures

📚 Practical Examples

  • Optimize a Sorting Algorithm
    Compare QuickSort vs. MergeSort in real-world scenarios.

    Sorting_Algorithm_Comparison

  • Implement Dijkstra's Algorithm
    Step-by-step guide with code snippets and visualizations.

    Dijkstra_Algorithm_Implementation

🌐 Expand Your Knowledge

For deeper insights into advanced algorithms, check out our Module 3: Advanced Algorithms playlist. It includes video tutorials and coding challenges to reinforce your learning! 💡

⚠️ Stay Compliant

Always ensure your use of algorithms adheres to ethical guidelines and legal standards. For more on responsible AI practices, visit our Ethics Guide.