Phase 2: Data Structures & Algorithms

Master core data structures and algorithms essential for technical interviews and efficient code design.

The curriculum is public. Reading these lessons requires access to the corresponding paid track. Compare access and pricing.

What will you learn?

• Implement common data structures
• Analyze algorithm complexity

Lessons and practice

1. Lesson 1: Why Algorithms Matter
2. Lesson 2: Big-O Basics
3. Lesson 3: Logarithmic Complexity
4. Lesson 4: Advanced Complexities
5. Lesson 5: Space Complexity
6. Lesson 6: Complexity Cheat Sheets
7. Lesson 1: What is a Linked List?
8. Lesson 2: Core Operations & Complexity
9. Lesson 3: Advanced Linked Lists
10. Lesson 4: Two-Pointer Interview Patterns
11. Lesson 5: Advanced System Design (LRU Cache)
12. Linked Lists Practice Problems
13. Linked Lists Cheatsheet
14. Linked Lists - FAANG Interview Questions
15. Lesson 1: The Sliding Window Pattern
16. Lesson 2: Two Pointers Pattern
17. Lesson 3: Prefix Sum Pattern
18. Advanced Patterns - Practice Problems
19. Advanced Patterns - Quick Reference Cheatsheet
20. Advanced Patterns - Interview Success Guide
21. Lesson 1: What is a Stack?
22. Lesson 2: What is a Queue?
23. Lesson 3: Stack Interview Patterns
24. Stacks & Queues - Practice Problems
25. Stacks & Queues - Quick Reference Cheatsheet
26. Stacks & Queues - FAANG Interview Questions
27. Lesson 1: Introduction to Trees
28. Lesson 2: Tree Traversals (DFS & BFS)
29. Lesson 3: Binary Search Trees (BST)
30. Trees & BST - Practice Problems
31. Trees & BST - Quick Reference Cheatsheet
32. Trees & BST - FAANG Interview Questions
33. Lesson 1: What is a Heap?
34. Lesson 2: Heap Operations (Push & Pop)
35. Lesson 3: Heap Interview Patterns
36. Heaps Practice Exercises
37. Heaps Quick Reference Cheatsheet
38. Heaps Interview Questions
39. Lesson 1: What is Dynamic Programming?
40. Lesson 2: Memoization vs Tabulation
41. Lesson 3: DP Interview Patterns
42. Dynamic Programming Practice Problems
43. Dynamic Programming Cheatsheet
44. Dynamic Programming Interview Questions
45. Lesson 1: Introduction to Graphs
46. Lesson 2: Representing Graphs in Code
47. Lesson 3: Searching Graphs (BFS & DFS)
48. Graphs Practice Problems
49. Graphs Cheatsheet
50. Graphs Interview Questions
51. Lesson 1: What is Recursion?
52. Lesson 2: What is Backtracking?
53. Lesson 3: Recursion Interview Patterns
54. Recursion & Backtracking Practice Problems
55. Recursion & Backtracking Cheatsheet
56. Recursion & Backtracking Interview Questions
57. Lesson 1: What is a Greedy Algorithm?
58. Lesson 2: When Greedy Algorithms Fail
59. Lesson 3: Greedy Interview Patterns
60. Greedy Algorithms Practice Exercises
61. Greedy Algorithms Quick Reference
62. Greedy Algorithms Interview Questions
63. Lesson 1: What is a Trie?
64. Lesson 2: Trie Operations (Insert & Search)
65. Tries - Practice Problems
66. Tries - Quick Reference Cheatsheet
67. Tries - Interview Success Guide

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