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Computer Science Fundamentals Beginner

Algorithms Analysis

A comprehensive, beginner-friendly guide to learning Algorithms Analysis. Master the fundamentals and build real-world projects.

30 chapters 7h 30m 4.7 (218)
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What you'll learn

  • Introduction to Algorithms
  • Time Complexity and Space Complexity
  • Big O, Big Omega, and Big Theta
  • Asymptotic Analysis
  • Recursion and Recursive Algorithms
  • Divide and Conquer Algorithms
  • Brute Force Algorithms
  • Searching Algorithms Fundamentals

Course content

30 chapters Β· 7h 30m
  1. 1 Introduction to Algorithms 15 min
  2. 2 Time Complexity and Space Complexity 15 min
  3. 3 Big O, Big Omega, and Big Theta 15 min
  4. 4 Asymptotic Analysis 15 min
  5. 5 Recursion and Recursive Algorithms 15 min
  6. 6 Divide and Conquer Algorithms 15 min
  7. 7 Brute Force Algorithms 15 min
  8. 8 Searching Algorithms Fundamentals 15 min
  9. 9 Linear Search Algorithm 15 min
  10. 10 Binary Search Algorithm 15 min
  11. 11 Sorting Algorithms Introduction 15 min
  12. 12 Bubble Sort Algorithm 15 min
  13. 13 Selection Sort Algorithm 15 min
  14. 14 Insertion Sort Algorithm 15 min
  15. 15 Merge Sort Algorithm 15 min
  16. 16 Quick Sort Algorithm 15 min
  17. 17 Heap Sort Algorithm 15 min
  18. 18 Counting Sort and Radix Sort 15 min
  19. 19 Greedy Algorithms 15 min
  20. 20 Dynamic Programming Fundamentals 15 min
  21. 21 Backtracking Algorithms 15 min
  22. 22 Graph Theory Introduction 15 min
  23. 23 Breadth-First Search (BFS) 15 min
  24. 24 Depth-First Search (DFS) 15 min
  25. 25 Minimum Spanning Trees (MST) 15 min
  26. 26 Shortest Path Algorithms (Dijkstra) 15 min
  27. 27 Bellman-Ford Algorithm 15 min
  28. 28 Bit Manipulation Algorithms 15 min
  29. 29 Interview Preparation and Optimization Strategies 15 min
  30. 30 Capstone Project - The High-Speed Trading Engine 15 min