Core DSA | Algorithms for AI

📄️ Two Pointers

From converging pointers to Floyd's cycle detection — turning O(n²) scans into O(n) passes.

Fixed and variable-size windows for subarray/substring problems, explained at conceptual and implementation levels.

From 'guess the number' to allocating resources under constraints — plus the binary-search-on-answer paradigm.

Engineering judgment for choosing sorts: stability, in-place tradeoffs, and what your standard library actually does.

LIFO/FIFO structures plus the monotonic stack/queue pattern for interview and production use.

Binary heaps from first principles to production — top-K, streaming medians, and scheduler design.

Basic trees and BSTs from first-principles intuition to expert AI/ML/LLM connections.

Breadth-first and depth-first search from first principles to LLM reasoning systems.

Prefix-sum hashing and complement hashing — two of the highest-leverage patterns in algorithmic problem solving.

Interactive practice for BFS & DFS — animated walkthrough and a live Python exercise.

Interactive practice for Binary Search — animated walkthrough and a live Python exercise.

Interactive practice for Hashing Patterns — a live in-browser Python exercise.

Interactive practice for Heaps & Priority Queues — animated walkthrough and a live Python exercise.

Interactive practice for Sliding Window — animated walkthrough and a live Python exercise.

Interactive practice for Sorting Algorithms — animated walkthrough and a live Python exercise.

Interactive practice for Stacks & Queues — animated walkthrough and a live Python exercise.

Interactive practice for Trees & BST — animated walkthrough and a live Python exercise.

Interactive Two Pointers practice — animated walkthrough plus a live Python coding exercise.