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Hand-written tutorials, ordered as a recommended learning path.

1. 21 Partition LL Master linked list partitioning — partition around a value (LeetCode 86), odd-even rearrangement (LeetCode 328), segregate 0s/1s/2s, with full Python implementations and Big-O analysis. 12 min read →
2. 22 Rotate & Swap Master linked list rotation by K positions, swap nodes in pairs, and swap Kth nodes from both ends — full Python implementations, step-by-step traces, and Big-O analysis. 13 min read →
3. 23 LL Interview Guide Master the top 15 linked list interview patterns — dummy node, fast-slow pointers, reversal, merge, partition, and more. Includes common mistakes, a time complexity cheatsheet, and a decision flowchart. 14 min read →
4. 24 Skip Lists Understand skip lists — multi-level linked lists with probabilistic balancing that achieve O(log n) search, insert, and delete. Covers the concept, comparison with BSTs, Redis use case, and full Python implementation. 15 min read →
5. 25 What Is DSA? A beginner-friendly introduction to data structures and algorithms — what they are, why they matter for interviews and real performance, and how to actually start learning DSA. 9 min read →
6. 26 Big-O Notation A practical guide to Big-O notation — O(1), O(log n), O(n), O(n log n), O(n^2), and beyond, with code examples, best/average/worst case, and a brief look at amortized and space complexity. 11 min read →
7. 27 Arrays — Intro A beginner's introduction to arrays — contiguous memory, indexing, the Python list vs C array caveat, time complexity of read/write/insert/delete, and 1D vs 2D arrays. 10 min read →
8. 28 Arrays — Operations The everyday array patterns every DSA learner should know — traversal, linear search, insertion, deletion, reversal, rotation, prefix sums, Kadane's preview, and the one-pass habit. 11 min read →
9. 29 Arrays — Practice Ten classic array interview problems with examples, approach, complexity, and clean Python solutions — Two Sum, Best Time to Buy/Sell Stock, Kadane's, Rotate Array, Product Except Self, and more. 13 min read →
10. 30 Expression Evaluation Build a calculator from scratch — learn infix, prefix, and postfix notation, the Shunting Yard algorithm, postfix evaluation, and Python implementation. 8 min read →
11. 31 Strings — Intro An introduction to strings for data structures and algorithms — immutability, indexing, slicing, common operations, ASCII versus Unicode, and the two-pointer and frequency-counter patterns you will use everywhere. 8 min read →
12. 32 Pattern Matching A practical tour of substring search — the naive O(n·m) scan, the KMP algorithm with its LPS array, and the Rabin-Karp rolling hash. Worked examples, code, and intuition for when to use each. 8 min read →
13. 33 Strings — Practice Eight classic string problems with worked Python solutions — Valid Anagram, Group Anagrams, Longest Substring Without Repeating Characters, Longest Palindromic Substring, and more. 9 min read →
14. 34 Hashing & Hash Maps How hash functions, hash maps, and hash sets work — the intuition behind buckets and collisions, chaining vs open addressing, average and worst-case complexity, and the Python containers built on them. 9 min read →
15. 35 Hashing — Practice Eight classic hash map problems with worked Python solutions — Two Sum, Group Anagrams, Subarray Sum Equals K, Longest Consecutive Sequence, Top K Frequent Elements, and more. 10 min read →
16. 36 Next Greater Element Master the monotonic stack pattern — solve Next Greater Element, Next Smaller, stock span, and circular array variants with Python templates and visual walkthroughs. 9 min read →
17. 37 Linked Lists — Intro A practical introduction to linked lists — what a node is, singly vs doubly linked, head and tail, how arrays and linked lists differ, and a clean Python implementation you can build on. 9 min read →
18. 38 LL Operations The core operations every linked list problem builds on — inserting at head/tail/middle, deleting by value, reversing iteratively and recursively, finding the middle, and detecting a cycle. 10 min read →
19. 39 LL — Practice Eight classic linked-list interview problems — reverse, detect cycle, merge sorted lists, remove Nth from end, cycle start, palindrome, add two numbers, and intersection — each with a worked Python solution. 11 min read →
20. 40 Stacks & Queues A practical introduction to stacks and queues — LIFO vs FIFO, using a Python list as a stack, collections.deque as a queue, and the real-world problems each one solves cleanly. 10 min read →