DSA Interview Prep 12-Week Study Plan 2026

You know that awful feeling when a recruiter says, “Next step is a coding interview,” and your brain immediately starts whispering, “Cool, so I’ll just forget how arrays work in public.”

If you’re aiming for software engineering roles at companies like Google, Meta, Amazon, Microsoft, Stripe, Datadog, Booking.com, Shopify, Revolut, or Klarna in 2026, data structures and algorithms are still very much alive. Annoying? Sometimes. Useful? Also yes. And for many roles, especially new grad, backend, platform, infrastructure, and full-stack roles, DSA can be the gate between you and a salary jump from $85k to $180k in the US, or from €55k to €120k in parts of Europe.

DSA Interview Prep 12-Week Study Plan 2026#

This 12-week plan is built for normal humans.

Not mythical people who wake up at 5:00 a.m., solve 12 LeetCode hards before breakfast, journal about gratitude, and still have time to make sourdough.

You can use this plan if:

1. You work full-time and can study 6 to 10 hours per week.
2. You are a student preparing for internships or graduate roles.
3. You have coding experience but feel rusty on algorithms.
4. You keep jumping between random YouTube videos and feel lost.
5. You want structure, not panic.

The goal is simple: by the end of 12 weeks, you should be able to walk into most DSA interviews and say, “Okay, I’ve seen this pattern before.”

Not every problem. Not every trick. But enough patterns to stay calm, reason clearly, and write working code under pressure.

What DSA Interviews Look Like In 2026#

Most companies still test the same core ideas.

A typical coding interview includes:

1. One or two problems in 45 to 60 minutes.
2. A shared editor like CoderPad, CodeSignal, HackerRank, or Karat.
3. Follow-up questions about complexity.
4. Edge cases.
5. Sometimes, system design for mid-level and senior roles.

At companies like Amazon, Microsoft, Uber, Wise, and Bloomberg, you may see a mix of:

• Arrays and strings
• Hash maps
• Two pointers
• Sliding window
• Trees and graphs
• Dynamic programming
• Recursion and backtracking
• Heaps and priority queues
• Binary search
• Sorting and intervals

For salaries, the stakes are real.

In the US, software engineer roles often pay:

• Entry-level: $90k to $140k base salary
• Mid-level: $130k to $190k base salary
• Senior: $170k to $250k base salary
• Big Tech total compensation: often $180k to $450k+

In Europe, you might see:

• Berlin: €65k to €120k for many SWE roles
• Amsterdam: €70k to €130k
• London: £70k to £160k, higher at US tech firms
• Dublin: €70k to €140k
• Zurich: CHF 120k to CHF 220k

So yes, practicing linked lists at 9:30 p.m. can feel silly. But if it helps you land a role at Meta, Apple, Adyen, Spotify, or Snowflake, it can pay for itself very quickly.

The Weekly Time Commitment#

You do not need to study 40 hours per week.

Actually, please do not do that unless you enjoy burnout and eye twitching.

A realistic weekly schedule:

1. Light plan: 5 hours per week
   Good if you have a job, kids, exams, or a life.

2. Standard plan: 8 to 10 hours per week
   Best for most people. Enough to improve without falling apart.

3. Aggressive plan: 15 hours per week
   Useful if interviews are already scheduled within 2 to 3 months.

A good weekly split:

• 2 hours learning concepts
• 4 to 6 hours solving problems
• 1 hour reviewing mistakes
• 1 hour mock interview or timed practice

The review hour is where the magic happens.

Most people do 80 problems badly and remember almost nothing. You are better off doing 40 problems, reviewing them properly, and understanding the patterns.

Before Week 1: Set Up Your Prep System#

Before you start grinding, build a simple system.

You need:

1. A coding platform
   Use LeetCode, NeetCode, CodeSignal, HackerRank, or AlgoExpert.

2. A note-taking place
   Notion, Google Docs, Obsidian, or even a spreadsheet is fine.

3. A target language
   Pick one language and stick to it.

4. A problem tracker
   Track problem name, pattern, difficulty, mistakes, and whether you solved it alone.

5. A review schedule
   Revisit missed problems after 2 days, 1 week, and 3 weeks.

Best coding languages for DSA interviews:

• Python: easiest for speed and readability
• Java: common for enterprise and backend roles
• JavaScript or TypeScript: fine for full-stack roles
• C++: strong for performance-heavy interviews, but more syntax stress

If you are unsure, pick Python.

A lot of people overthink this and spend two weeks deciding between Java and Python. That is just procrastination wearing a nice coat.

Your Problem-Solving Template#

Use the same process every time.

In an interview, your structure matters almost as much as your final answer.

Follow this:

1. Restate the problem.
2. Ask clarifying questions.
3. Give a brute-force approach.
4. Improve the solution.
5. Explain time and space complexity.
6. Code carefully.
7. Test with examples.
8. Check edge cases.

Say things like:

• “Let me first confirm the input constraints.”
• “A brute-force solution would be...”
• “We can improve this by using a hash map.”
• “The time complexity is O(n) because we scan the array once.”
• “Let me test this on an empty input and a single-item input.”

This makes you sound calm, even when your soul is doing parkour.

Weeks 1 and 2: Arrays, Strings, Hash Maps#

This is your foundation.

If you are weak here, everything else becomes more painful. Arrays and hash maps show up constantly because they are simple to ask, easy to scale, and great for testing basic reasoning.

What to learn

Focus on:

1. Array traversal
2. String manipulation
3. Frequency counting
4. Prefix sums
5. Hash maps and hash sets
6. Basic sorting
7. Time complexity basics

Problems to practice

Start with easy and medium problems like:

• Two Sum
• Contains Duplicate
• Valid Anagram
• Group Anagrams
• Product of Array Except Self
• Top K Frequent Elements
• Encode and Decode Strings
• Longest Consecutive Sequence
• Valid Palindrome
• Roman to Integer

Weekly target

For each of these two weeks:

• 8 to 12 problems
• 2 timed sessions
• 1 review session

What you should be able to do by end of Week 2

You should be comfortable saying:

• “This needs a hash map.”
• “This can be solved by counting frequencies.”
• “Sorting changes the complexity to O(n log n).”
• “A prefix sum helps avoid repeated work.”

Common mistake

Beginners often try to memorize exact solutions.

Do not do that.

Instead, remember triggers:

• “Need to find pairs fast” means hash map.
• “Need counts” means frequency map.
• “Repeated range sums” means prefix sum.
• “Need uniqueness” means set.

This pattern recognition is what gets you paid.

Weeks 3 and 4: Two Pointers, Sliding Window, Stack#

Now you start solving problems that feel clever.

These topics are common at companies like Amazon, Expedia, PayPal, Microsoft, and many fintech firms because they test whether you can optimize beyond brute force.

What to learn

Focus on:

1. Two pointers from both ends
2. Fast and slow pointers
3. Fixed-size sliding window
4. Variable-size sliding window
5. Monotonic stacks
6. Parentheses and expression problems

Problems to practice

Good problems include:

• 3Sum
• Container With Most Water
• Trapping Rain Water
• Best Time to Buy and Sell Stock
• Longest Substring Without Repeating Characters
• Minimum Window Substring
• Valid Parentheses
• Daily Temperatures
• Evaluate Reverse Polish Notation
• Min Stack

Weekly target

Each week:

• 10 to 14 problems
• 1 longer review block
• 1 timed 45-minute mock problem

What you should notice

Sliding window problems usually ask for:

• Longest subarray
• Shortest subarray
• Maximum sum
• Minimum length
• Unique characters
• At most K distinct values

Stack problems often involve:

• “Next greater”
• “Previous smaller”
• Nested structures
• Matching symbols
• Undo-like behavior

Common mistake

With sliding window, people often move the wrong pointer.

Use this mental model:

1. Expand right pointer to include more.
2. If the window becomes invalid, move left pointer.
3. Update the answer at the correct moment.

Sounds simple. Still ruins lives in interviews.

Week 5: Binary Search and Sorting Patterns#

Binary search is not just “find a number in a sorted array.”

In interviews, binary search often means finding the smallest or largest value that satisfies a condition.

That sounds fancy, but it is usually a yes/no problem in disguise.

What to learn

Focus on:

1. Standard binary search
2. Search in rotated sorted arrays
3. Lower bound and upper bound
4. Binary search on answer
5. Sorting with custom comparators
6. Merge intervals

Problems to practice

Try:

• Binary Search
• Search in Rotated Sorted Array
• Find Minimum in Rotated Sorted Array
• Time Based Key-Value Store
• Koko Eating Bananas
• Median of Two Sorted Arrays, optional hard
• Merge Intervals
• Insert Interval
• Non-overlapping Intervals
• Meeting Rooms

Weekly target

• 8 to 10 problems
• 3 binary search variations
• 3 interval problems
• 1 timed mock

What interviewers like here

They want to see if you can:

• Define search boundaries
• Avoid infinite loops
• Handle off-by-one errors
• Explain why the condition works

If you hate binary search, welcome to the club. Everyone has written mid = left + right / 2 wrong at least once.

Weeks 6 and 7: Trees, Recursion, Graph Basics#

This is where many candidates start sweating.

Trees and graphs can look scary because the code is less linear. But most interview tree problems are built around a few repeating ideas.

What to learn

For trees:

1. DFS preorder, inorder, postorder
2. BFS level order traversal
3. Recursion base cases
4. Tree height and depth
5. Binary search tree properties
6. Lowest common ancestor

For graphs:

1. Adjacency lists
2. Visited sets
3. DFS
4. BFS
5. Connected components
6. Cycle detection basics

Problems to practice

Trees:

• Invert Binary Tree
• Maximum Depth of Binary Tree
• Diameter of Binary Tree
• Balanced Binary Tree
• Same Tree
• Subtree of Another Tree
• Binary Tree Level Order Traversal
• Lowest Common Ancestor of BST
• Validate Binary Search Tree
• Kth Smallest Element in BST

Graphs:

• Number of Islands
• Clone Graph
• Max Area of Island
• Pacific Atlantic Water Flow
• Course Schedule
• Rotting Oranges
• Walls and Gates
• Graph Valid Tree

Weekly target

Each week:

• 10 to 12 problems
• Draw every graph or tree before coding
• Practice explaining recursive calls out loud

Recursion tip

Every recursive solution needs:

1. A base case
2. Work at the current node
3. Recursive calls
4. Return value

If you cannot explain what your function returns, stop coding.

Seriously. That is where bugs breed.

Week 8: Heaps, Priority Queues, and Greedy#

Heaps are common in scheduling, ranking, streaming data, and “top K” problems.

Companies like Uber, DoorDash, Instacart, Netflix, and Amazon love these because they map well to real systems: orders, routes, feeds, recommendations, and resource allocation.

What to learn

Focus on:

1. Min heaps
2. Max heaps
3. Top K patterns
4. K-way merge
5. Greedy choice
6. Scheduling problems

Problems to practice

Try:

• Kth Largest Element in an Array
• Last Stone Weight
• K Closest Points to Origin
• Find Median from Data Stream
• Merge K Sorted Lists
• Task Scheduler
• Meeting Rooms II
• Reorganize String
• Jump Game
• Gas Station

Weekly target

• 8 to 10 problems
• 2 top K problems
• 2 scheduling problems
• 2 greedy problems
• 1 mock interview

Common mistake

People reach for a heap when sorting is enough.

Ask:

• Do I need all items sorted? Sort.
• Do I only need the top K? Heap.
• Do I need dynamic updates? Heap.

That small decision can make your solution cleaner and faster.

Weeks 9 and 10: Dynamic Programming Without Crying#

Dynamic programming has a reputation.

Fair enough. It can be weird.

But for interviews, DP usually means: “Can you break this problem into smaller repeated decisions?”

You do not need to become a competitive programming wizard. You need to handle common DP patterns with confidence.

What to learn

Focus on:

1. 1D DP
2. 2D DP
3. Memoization
4. Tabulation
5. Decision trees
6. Subsequence problems
7. Grid problems
8. Knapsack-style choices

Problems to practice

Start with:

• Climbing Stairs
• Min Cost Climbing Stairs
• House Robber
• House Robber II
• Coin Change
• Longest Increasing Subsequence
• Word Break
• Combination Sum IV
• Unique Paths
• Longest Common Subsequence
• Partition Equal Subset Sum

Optional harder problems:

• Edit Distance
• Burst Balloons
• Regular Expression Matching

Weekly target

Each week:

• 8 to 10 DP problems
• Write recurrence before coding
• Solve with memoization first
• Convert some to bottom-up only if useful

The DP question checklist

Ask yourself:

1. What are the choices?
2. What changes after each choice?
3. What state do I need to represent?
4. What is the base case?
5. What value am I returning?
6. Are subproblems repeated?

For example, in Coin Change:

• Choice: pick a coin
• State: remaining amount
• Base case: amount is 0
• Return: minimum number of coins

That is DP. Not magic. Just organized suffering.

Week 11: Mixed Practice and Weak Spots#

By Week 11, stop learning brand-new topics unless there is a huge gap.

Now your job is to mix patterns so your brain does not depend on labels.

In real interviews, nobody says, “Hello, this is a sliding window problem.” Rude, but true.

What to do this week

Run mixed practice sessions.

Example schedule:

1. Monday: 2 medium problems, random topics
2. Tuesday: Review missed problems
3. Wednesday: 1 timed problem, 45 minutes
4. Thursday: 2 graph or tree problems
5. Friday: 1 DP problem, 1 array problem
6. Saturday: Mock interview
7. Sunday: Rest and review notes

Build your personal weak list

Make a list with columns:

• Problem name
• Topic
• Why I missed it
• Correct pattern
• Key insight
• Retry date

Common “why I missed it” examples:

• Did not identify sliding window
• Forgot visited set
• Wrong base case
• Off-by-one error
• Did not handle duplicates
• Bad complexity
• Could not explain approach clearly

This list is gold.

Do not hide from it. Your weak list is basically your interview improvement plan yelling politely.

Week 12: Interview Simulation Week#

This week is about performance.

You may know the topics, but can you solve while someone watches, asks questions, and silently judges your variable names? That is the real test.

Your Week 12 schedule

Do this:

1. 3 mock interviews
2. 4 timed medium problems
3. 1 easy warm-up per day
4. Review all top mistakes
5. Prepare your interview opening script
6. Sleep properly before real interviews

Use platforms like:

• Pramp
• interviewing.io
• LeetCode mock assessment
• Meetapro
• Exponent
• A friend who will not be too nice

Mock interview format

For each mock:

1. 5 minutes: problem clarification
2. 10 minutes: approach discussion
3. 20 to 25 minutes: coding
4. 5 to 10 minutes: testing and complexity
5. 10 minutes: feedback

Record yourself if possible.

Yes, it is uncomfortable. You will hear yourself say “uhh” 400 times. Still useful.

What to practice saying

Use calm language:

• “I’ll start with a brute-force approach, then optimize.”
• “The bottleneck here is repeated scanning.”
• “A hash map can help store what we have already seen.”
• “Let me test against an edge case.”
• “I’m going to adjust this because I see a duplicate issue.”

Interviewers do not expect perfection.

They want signal that you can think, communicate, and recover when stuck.

How Many Problems Should You Solve?#

A good target for 12 weeks is 100 to 140 problems.

You can pass interviews with fewer if your review is strong. You can fail with 300 if you are just copying solutions and collecting green checkmarks like Pokémon.

A balanced number:

• Easy: 25 to 35
• Medium: 65 to 90
• Hard: 10 to 15

Spend most of your time on mediums.

Hard problems are useful, but do not let them destroy your morale. If a hard takes 90 minutes and teaches you one rare trick, fine. If it ruins your evening and makes you question your degree, move on.

Best DSA Resources For 2026#

Here are practical resources that people actually use.

Free resources

1. NeetCode 150
   Great structured problem list.

2. LeetCode free problems
   Still the main practice ground.

3. CS50 and MIT OpenCourseWare
   Good if your fundamentals are shaky.

4. YouTube channels
   NeetCode, Abdul Bari, WilliamFiset, freeCodeCamp, and Tech With Tim.

5. VisuAlgo
   Great for visualizing data structures.

Paid resources

1. LeetCode Premium
   Useful for company-tagged questions, often around $35/month.

2. AlgoExpert
   Structured explanations, but not required.

3. Educative.io
   Good for pattern-based learning.

4. interviewing.io
   Useful for serious mock interviews.

You do not need every subscription.

Pick one main platform and stick with it. Resource hopping feels productive, but it usually means you are avoiding the next problem.

How To Study If You Have A Full-Time Job#

If you work full-time, your plan needs to be boring and repeatable.

Try this schedule:

Monday to Friday

• 30 minutes before work or lunch: one easy or review problem
• 45 minutes in the evening: one medium problem
• 10 minutes: write notes on mistakes

Do that 3 days per week, not 5, if you are tired.

Weekend

• Saturday: 2-hour deep session
• Sunday: 1-hour review and one timed problem

That gives you around 6 to 8 hours per week.

Enough.

The trick is not heroic effort. It is not disappearing for one weekend and solving 38 problems while eating cereal from a mug.

The trick is showing up again and again.

What To Do When You Get Stuck#

You will get stuck.

That does not mean you are bad at coding. It means the problem is doing its job.

Use the 20-minute rule:

1. Try seriously for 20 minutes.
2. If stuck, read only the first hint.
3. Try again for 10 minutes.
4. If still stuck, read the solution idea, not the code.
5. Code it yourself.
6. Re-solve it 2 days later.

Do not stare at a problem for 2 hours trying to prove character.

That is not discipline. That is just pain with a keyboard.

How To Review A Problem Properly#

After each problem, write:

1. What was the pattern?
2. What was the key insight?
3. What mistake did I make?
4. What is the time complexity?
5. What is the space complexity?
6. Could I explain this to another person?

Example note:

• Problem: Longest Substring Without Repeating Characters
• Pattern: Sliding window
• Mistake: Moved left pointer only once instead of until valid
• Key insight: Maintain a set or map of current window characters
• Complexity: O(n) time, O(k) space

This takes 3 minutes.

Those 3 minutes are worth more than solving another problem badly.

Red Flags In Your Prep#

Watch for these.

You might be prepping wrong if:

1. You only watch videos and rarely code.
2. You look at solutions too quickly.
3. You never review old problems.
4. You avoid topics you hate.
5. You cannot explain time complexity.
6. You solve only easy problems.
7. You panic when problems are mixed.
8. You memorize code instead of patterns.

If that is you, no drama. Just adjust.

DSA prep is like gym training. Bad reps still make you tired, but they do not build what you need.

Company-Specific Prep Tips#

Different companies have different flavors.

Google

Expect strong problem solving, clean reasoning, and follow-ups. Medium to hard problems are common.

Typical total compensation in the US can reach $180k to $300k+ for early and mid-level roles, with senior roles much higher.

Amazon

Expect DSA plus behavioral questions based on Leadership Principles.

US SWE roles often range from $130k to $250k+ total compensation, depending on level and location.

Meta

Expect speed and pattern recognition. You may get two problems in one interview.

US total compensation for software engineers can range from $180k to $350k+.

Microsoft

Often balanced interviews with DSA, design, and practical coding judgment.

US salaries commonly range from $120k to $220k+ total compensation for many levels.

Booking.com, Adyen, Spotify, Klarna, Revolut

In Europe, expect coding rounds plus practical engineering discussions.

Compensation varies widely, but strong candidates may see:

• Amsterdam: €80k to €140k
• Stockholm: SEK 700k to SEK 1.3M
• London: £80k to £180k
• Berlin: €75k to €130k

For US-based remote companies hiring in Europe, compensation can be even higher.

The Final 12-Week Checklist#

By the end of your plan, you should have:

1. Solved 100 to 140 problems.
2. Reviewed every missed problem.
3. Completed at least 4 mock interviews.
4. Practiced all major patterns.
5. Built a weak-spots list.
6. Timed yourself repeatedly.
7. Learned to explain complexity clearly.
8. Practiced speaking while coding.
9. Prepared examples for behavioral questions.
10. Cleaned up your resume before applying.

That last one matters more than people think.

You can be great at DSA, but if your resume gets rejected before the recruiter call, nobody will ever admire your beautiful graph traversal.

Your 2026 DSA Prep Mindset#

You do not need to be a genius.

You need pattern recognition, calm communication, and enough reps that your brain stops treating every problem like a personal attack.

Some days you will solve a medium in 22 minutes and feel unstoppable.

Other days an easy problem will bully you in front of your coffee.

Both are normal.

Stick to the plan. Review your misses. Practice out loud. Do timed sessions. Get feedback before the real interview.

And please, do not wait until the night before your Google interview to learn dynamic programming. Future you deserves better.

Before you send out applications, make sure your resume can actually get you into those interviews. Run it through JobRise’s free ATS checker here: https://jobrise.io/en/free-ats-checker/