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How to Prepare for FAANG Interviews in 3 Months: A Week-by-Week Plan

14 min read

Three months is enough time to go from "I sort of remember data structures from college" to confidently solving medium-hard LeetCode problems in 30 minutes. But only if you study the right things in the right order. Most people fail not because they lack talent, but because they grind random problems without a plan.

This guide gives you that plan. It is built on a pattern-first philosophy: instead of memorizing 300 individual problems, you learn the 15–20 reusable patterns that cover 90% of interview questions. Each week targets specific patterns, with curated problems to reinforce them.

What you need before starting

  • Basic programming in at least one language (Python, Java, C++, or JavaScript)
  • Familiarity with arrays, strings, linked lists, stacks, queues, and hash maps
  • 2–3 hours of focused study time per day
  • A LeetCode account (free tier is fine) and a notebook for notes

Month 1: Build the Foundation (Weeks 1–4)

The first month is about mastering the patterns that appear in 60%+ of all coding interviews: Two Pointers, Sliding Window, Binary Search, and BFS/DFS. These are the bread and butter — get them right and you already have a fighting chance at any FAANG interview.

The order matters. Two Pointers and Hash Maps are the easiest to internalize and give you quick wins. Sliding Window builds directly on Two Pointers. Binary Search adds a different thinking mode (halving search space). BFS/DFS round out the month with graph and tree traversal — the other major problem category after arrays.

Month 2: Level Up (Weeks 5–8)

Now you tackle the patterns that separate "pass" from "strong hire": Dynamic Programming, Backtracking, Topological Sort, Monotonic Stack, and Trie. These patterns feel harder at first, but they follow templates just like the foundational ones.

DP is where most candidates struggle. The key insight: if the problem asks "how many ways" or "minimum cost" and earlier decisions affect later ones, it is almost certainly DP. Start with the Fibonacci pattern before moving to Knapsack and grid DP. Do not skip the easy problems — they build the muscle memory you need for harder variants.

Month 3: Polish and Perform (Weeks 9–12)

The final month shifts from learning to performing. You solve mixed problems without knowing the pattern in advance, take timed mock interviews, learn basic system design, and prepare behavioral answers. This is where everything comes together.

The biggest mistake candidates make in month 3 is continuing to grind new problems instead of reviewing and reinforcing what they already know. A candidate who has deeply mastered 80 problems across 15 patterns will outperform someone who has superficially seen 200 problems every time.

The Complete 12-Week Schedule

Week 1: Two Pointers & Hash Maps

Month 1

Build a foundation with O(n) array techniques. Get comfortable with pointer manipulation and hash-based lookups.

Patterns: Two Pointers, Hash Map / Counting

Key problems: Two Sum · Valid Palindrome · 3Sum · Container With Most Water · Group Anagrams

Week 2: Sliding Window

Month 1

Master the expand-right / shrink-left template for subarray and substring problems.

Patterns: Sliding Window

Key problems: Best Time to Buy and Sell Stock · Longest Substring Without Repeating Characters · Minimum Window Substring · Permutation in String

Week 3: Binary Search

Month 1

Go beyond simple search. Learn binary search on the answer space for optimization problems.

Patterns: Binary Search

Key problems: Binary Search · Search in Rotated Sorted Array · Find Minimum in Rotated Sorted Array · Koko Eating Bananas

Week 4: BFS & DFS Fundamentals

Month 1

Internalize the queue-based BFS template and recursive DFS pattern for trees and grids.

Patterns: BFS, DFS

Key problems: Number of Islands · Max Depth of Binary Tree · Binary Tree Level Order Traversal · Rotting Oranges

Week 5: Intro to Dynamic Programming

Month 2

Learn to spot overlapping subproblems. Practice both top-down (memo) and bottom-up (tabulation).

Patterns: Fibonacci DP, 0/1 Knapsack, Unbounded Knapsack

Key problems: Climbing Stairs · House Robber · Coin Change · Partition Equal Subset Sum

Week 6: Backtracking & Recursion

Month 2

Master the choose-explore-unchoose template for generating all valid configurations.

Patterns: Backtracking

Key problems: Subsets · Permutations · Combination Sum · Word Search

Week 7: Graph Algorithms

Month 2

Handle dependency ordering with Kahn's algorithm and connected-component problems with Union-Find.

Patterns: Topological Sort, Union-Find

Key problems: Course Schedule · Course Schedule II · Redundant Connection · Alien Dictionary

Week 8: Advanced Patterns

Month 2

Round out your pattern toolkit with stack-based, prefix-tree, and interval techniques.

Patterns: Monotonic Stack, Trie, Merge Intervals

Key problems: Daily Temperatures · Next Greater Element · Implement Trie · Merge Intervals · Insert Interval

Week 9: Mixed Practice & Weak Spots

Month 3

Solve problems without knowing the pattern in advance. Identify and drill your weakest areas.

Patterns: All previous patterns

Key problems: LRU Cache · Median of Two Sorted Arrays · Trapping Rain Water · Word Break

Week 10: System Design Basics

Month 3

Learn the framework: requirements → high-level design → deep dive → trade-offs. Focus on 3–5 classic designs.

Patterns: N/A — System Design

Key problems: Design URL Shortener · Design Twitter Feed · Design Rate Limiter

Week 11: Mock Interviews

Month 3

Simulate real conditions: timer, whiteboard (or shared editor), no IDE autocomplete.

Patterns: Timed practice across all patterns

Key problems: 2 full mock interviews per day (45 min each) · Review every solution afterward

Week 12: Behavioral & Final Review

Month 3

Nail the behavioral round. Review your notes, revisit tricky problems, and rest before the big day.

Patterns: STAR method, Leadership principles

Key problems: Prepare 5–8 STAR stories · Review top mistakes · Light coding to stay sharp

The Ideal Daily Routine (2–3 Hours)

Consistency beats intensity. Two focused hours every day is far more effective than a 10-hour weekend cram. Here is a daily structure that maximizes retention:

0:00–0:20

Review yesterday

Re-read your notes. Try to re-solve one problem from yesterday without looking at the solution. This spaced repetition is critical.

0:20–0:40

Learn the pattern

Read the pattern explanation on AlgoArk. Watch the animation. Understand the template and when to apply it.

0:40–2:00

Solve 2–3 problems

Start with an easy problem (10–15 min), then a medium (20–25 min). If time allows, attempt a hard. Set a timer — if you are stuck after 20 minutes, read the hint or editorial, then implement it yourself.

2:00–2:30

Write notes

For each problem, write: the pattern used, why that pattern applies, the key insight, and any mistakes you made. These notes are your secret weapon for week 12 review.

Why This Pattern Order Works

The order in this plan is not random. Each pattern builds on the ones before it:

  1. Two Pointers → Sliding Window: Sliding Window is essentially Two Pointers on a subarray. If you understand pointer manipulation, the window expansion/contraction logic clicks immediately.
  2. Binary Search: Introduces the concept of search space reduction — a different thinking mode from linear scans. It also appears inside other patterns later (e.g., binary search + greedy).
  3. BFS/DFS → Backtracking: Backtracking is DFS with constraint checking. You need DFS intuition first.
  4. DFS → Topological Sort: Topological sort is a specific DFS/BFS application on directed graphs. The graph traversal foundation from week 4 makes this natural.
  5. Easy DP → Hard DP: Fibonacci DP builds the mental model of "state depends on previous states." Once that clicks, Knapsack DP (adding a second dimension) is a logical next step.

Use the AlgoArk Roadmap to see these dependencies visualized as a learning path.

How Many Problems Should You Solve?

The short answer: 80–120 well-understood problems, not 300 barely-remembered ones.

Here is the breakdown by month:

~40

Month 1

Foundation patterns

~40

Month 2

Advanced patterns

~30

Month 3

Mixed + review

Quality means you can explain the approach, code it from scratch, and analyze its complexity — not just recognize the answer. After solving a problem, ask yourself: "If I saw a variation of this tomorrow, could I solve it without hints?" If not, you have not truly learned it.

5 Mistakes That Derail 3-Month Plans

1. Random grinding without a pattern focus

Solving random LeetCode problems is like studying for an exam by reading random textbook pages. Group problems by pattern instead. Use the Top 50 LeetCode by Pattern list as your curated problem set.

2. Spending too long on one problem

If you are stuck for more than 25 minutes, read the editorial. Understanding the solution and then implementing it yourself is far more valuable than staring at a blank screen for an hour.

3. Skipping behavioral prep

At FAANG companies, behavioral interviews carry equal weight. A candidate who aces coding but bombs behavioral will not get an offer. Prepare 5–8 STAR stories covering leadership, conflict, failure, and ambiguity.

4. Never doing timed practice

Solving a medium in 45 minutes at home is not the same as solving it in 25 minutes with someone watching. Start timed practice by week 8 at the latest. Use a 35-minute timer for mediums and 45 minutes for hards.

5. Ignoring system design entirely

Even for mid-level roles, many FAANG companies include a system design round. You do not need to be an expert — knowing the framework (requirements, high-level design, deep dive, trade-offs) and 3–5 classic designs is usually enough.

Resources and Tools

You do not need a dozen resources. Pick one primary tool for each category and stick with it:

Pattern Learning

AlgoArk Patterns — animated walkthroughs of all DSA patterns with code templates and complexity analysis. Free, no signup needed.

Pattern Recognition Practice

AlgoArk Quiz — read a problem description, pick the correct pattern. Builds the instant-recognition skill that interviewers test.

Decision Making

AlgoArk Decision Tree — answer 3–5 questions about a problem to identify the right pattern. Great when you are stuck.

Quick Reference

AlgoArk Cheat Sheet — one-page summary of all patterns with key indicators and complexities. Print it out and keep it on your desk during study sessions.

Curated Problem Lists

Top 50 LeetCode by Pattern — our hand-picked list of 50 problems organized by pattern, with difficulty ratings.

Final Tips for the Last Week

Do: Review your notes, re-solve 2–3 problems per day from your hardest patterns, practice explaining solutions out loud, get 8 hours of sleep.

Do not: Cram 50 new problems, pull all-nighters, change your language, or start learning a new pattern. Trust your preparation.

Related reads:

Start your 3-month journey today

Follow the roadmap, learn the patterns, and build the pattern recognition skill that gets you hired at FAANG.