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Data Structures and Algorithms — Full Course Syllabus

Core data structures and algorithms every developer should know, independent of any one language.

  1. 1. ArraysUnderstanding the array data structure and its properties.
  2. 2. Creating ArraysHow to create and initialize arrays in Python.
  3. 3. Array IndexingAccessing elements in an array using indices.
  4. 4. Hash TableA data structure that implements an associative array, mapping keys to values.
  5. 5. Depth-First Search (DFS)An algorithm for traversing or searching tree or graph data structures, exploring as far as possible along each branch.
  6. 6. Creating StacksHow to implement stacks using lists in Python.
  7. 7. Breadth-First Search (BFS)An algorithm for traversing or searching tree or graph data structures, exploring all neighbors at the present depth prior to moving on to nodes at the next depth level.
  8. 8. QueuesUnderstanding the queue data structure and its FIFO principle.
  9. 9. Sorting AlgorithmsUnderstanding various sorting algorithms like quicksort and mergesort.
  10. 10. Searching AlgorithmsUnderstanding searching algorithms like binary search and linear search.
  11. 11. RecursionUnderstanding the concept of recursion and its applications.
  12. 12. Big O NotationUnderstanding the concept of Big O notation for analyzing algorithm efficiency.
  13. 13. Time ComplexityA computational complexity that describes the amount of time it takes to run an algorithm.
  14. 14. Space ComplexityA computational complexity that describes the amount of memory space required by an algorithm.
  15. 15. Merge SortA divide-and-conquer algorithm that sorts an array by dividing it into halves, sorting them, and merging them back together.
  16. 16. Quick SortAn efficient sorting algorithm that selects a pivot and partitions the array into elements less than and greater than the pivot.
  17. 17. TreesUnderstanding tree data structures and their hierarchical nature.
  18. 18. Binary TreesUnderstanding binary trees and their properties.
  19. 19. Binary Search TreesUnderstanding binary search trees and their operations.
  20. 20. HeapsUnderstanding heap data structures and their properties.
  21. 21. GraphsUnderstanding graph data structures and their representation.
  22. 22. Graph Traversal AlgorithmsExploring different algorithms for traversing graphs, such as DFS and BFS.
  23. 23. Dynamic ProgrammingUnderstanding dynamic programming and its problem-solving techniques.