Interview Prep

Two pointers: palindrome check

Sliding window: max sum

Sliding window: longest unique substring

Hash maps: anagram check

Hash maps: two-sum

Binary search basics

Stack: valid parentheses

Linked list reversal

Tree DFS: max depth

Tree BFS: level order

Recursion: backtracking permutations

Dynamic programming: climbing stairs

Behavioral: the STAR framework

Hash map: subarray sum = K

Top K frequent elements

Three pointers: 3Sum

Binary search: first occurrence

Tree: lowest common ancestor

🎯 Review: Interview Prep module 2 recap

Graph BFS: shortest path in grid

Graph DFS: number of islands

DP: coin change

DP: longest increasing subsequence

System design lite: rate limiter

Heap: K closest points to origin

Heap: merge K sorted lists

Backtracking: combination sum

Backtracking: N-Queens

Backtracking: word search in grid

DP: edit distance (Levenshtein)

DP: 0/1 knapsack

DP: house robber

DP: longest common subsequence

Tries (prefix trees) — implementation

Tries: word search II

Union-Find / DSU pattern

Topological sort (Kahn's algorithm)

Dijkstra's shortest path

Greedy: meeting rooms II

🎯 Review: Interview Prep module 3 recap

Bit manipulation: XOR & masks

Math: prime sieve + Euclidean GCD

Stack: monotonic stack (next greater)

Behavioral: handling conflict (STAR)

Capstone: mock interview rubric

Graphs: Dijkstra shortest path

Graphs: Bellman-Ford with negative edges

Graphs: topological sort with cycle detection

Union-Find with path compression

Graphs: Kruskal MST

Segment tree: range sum + point update

Fenwick / Binary Indexed Tree

Trie: prefix autocomplete

DP hard: regex matching with .*

Longest Increasing Subsequence in O(n log n)

Sliding window: minimum window substring

Monotonic stack: largest rectangle in histogram

Two pointers: trapping rain water

Heaps: median from a stream

Binary search on answer: Koko bananas

🎯 Review: Interview Prep module 4 recap

System design: URL shortener

System design: news feed fan-out

Big-O proof: Master Theorem

Behavioral: a project that failed (STAR)

Capstone: thread-safe LRU cache with TTL

Detect cycle in a directed graph

Top-K frequent elements (heap)

Word Ladder (BFS shortest path)

Median from a data stream (two heaps)

Course schedule (topological sort)

Edit distance (Levenshtein DP)

Longest palindromic substring (expand around center)

Number of islands (grid DFS)

Trie autocomplete

Range sum query (Fenwick tree)

Behavioral: "How do you push back on an unrealistic deadline?"

Behavioral: "Disagree and commit"

System design: URL shortener (sketch)

System design: rate limiter (token bucket)

🏆 Interview Capstone: mock onsite — algorithm + behavioral

🎯 Review: Interview Prep module 5 recap

GIL: when threads help and when they don't

asyncio: event loop and await

asyncio.gather vs as_completed

Threading: race conditions and locks

Deadlock: Coffman's 4 conditions

Producer-consumer with queue.Queue

ML basics: bias-variance tradeoff

ML: logistic regression vs gradient boosting

ML: train/val/test split discipline

Behavioral: technical disagreement

Behavioral: ambiguity

OS: process vs thread vs coroutine

OS: virtual memory & page cache

Design patterns: Strategy

Design patterns: Dependency Injection

Networking: TCP vs UDP

Security: SQL injection prevention

Security: password hashing

Behavioral: receiving harsh PR feedback

🏆 Final capstone: interview prep checklist