Essential Algorithm Concepts for Coding Tests in 2020 + Practice Test Problem Solving

2. Concept of conditional statement

3. Conditional statement grammar (if)

4. Concept of loop

5. Grammar of loop statement: while

6. Grammar of loop statement: for

7. Understanding Multiple Loops

8. The concept of arrays

9. Concept of two-dimensional array

10. Enter values into an array and print them out

11. Find the maximum value

12. Array Summary

13. Understanding full search

14. Concept of time complexity

15. Example 1 of time complexity

16. Example 2 of time complexity

17. Execution time based on input size

18. Actual execution time of O(n)

19. Actual execution time of O(n^2)

20. Estimate the execution time

21. Time complexity of sorting

22. Basics of exhaustive search using recursive calls

23. Operation of exhaustive search using recursive calls

24. Code for exhaustive search using recursive calls

25. Example of exhaustive search using recursive calls

26. Basic Curriculum of Computer Engineering

27. Real life examples of data structures

28. Basic data structures - variables, arrays

29. Basic data structure - linked list

30. Summary of basic data structures

31. The concept of encapsulation

32. The concept of structure

33. Implementation of the structure

34. Maximum machine 1

35. Max Machine 2

36. Structure Terminology

37. Why use structures?

38. Basic data structure

39. Stack concept LIFO

40. Stack Overflow and Underflow

41. Stack Cleanup

42. Stack implementation 1

43. Stack implementation 2

44. Example 1: Determining if parentheses are correct

45. Queue concept FIFO

46. Queue Implementation 1

47. Queue implementation 2

48. Problems with queue implementation

49. The concept and implementation of circular queues

50. Implementation of a circular queue

51. The importance of meaning

52. The meaning of stack footprints

53. Meaning of stack Call stack

54. Stack semantic scheduling

55. Queue Meaning Scheduling

56. Stack, Queue Summary

57. Introduction to Graph

58. Mathematical knowledge related to graphs

59. Adjacency matrix

60. Advantages and disadvantages of adjacency matrices

61. Implementation of adjacency matrix 1

62. Implementation of adjacency matrix 2

63. Adjacency list

64. Pros and Cons of Adjacency Lists

65. Library

66. Standard Template Library (STL)

67. Vector Concepts and Basic Examples

68. Implementation of Vector 1

69. Vector initialization and methods

70. Implementation of Vector 2

71. Implementation of adjacency list

72. Meaning of graph traversal

73. Types of Graph Traversal DFS & BFS

74. The philosophy of depth-first exploration

75. Example of depth-first search

76. Depth-first search quiz

77. Full implementation of depth-first search

78. Detailed process of depth-first search

79. Implementation of depth-first search

80. Accuracy and time complexity of depth-first search

81. Breadth First Search

82. The concept of breadth-first search

83. Breadth-first search quiz

84. Implementation design of breadth-first search

85. STL QUEUE

86. Implementation of breadth-first search

87. Introduction to Graph Algorithms

88. Shortest path problem and algorithm (1)

89. Shortest path problem and algorithm (2)

90. Features of the shortest path

91. Introduction to Dijkstra's Algorithm

92. Dijkstra's algorithm

93. Implementation of Dijkstra's algorithm

94. Minimum spanning tree problem

95. Cut property

96. Kruskal's algorithm

97. Conditions for a cycle to occur

98. Introduction to disjoint sets

99. Implementation of disjoint sets using trees

100. Overall operation of Kruskal's algorithm

101. Implementation of Kruskal's algorithm