What is the most efficient 8-week coding interview study plan?
Weeks 1-2 should cover array, string, and hash map fundamentals. Weeks 3-4 should add trees, graphs, and recursion. Weeks 5-6 should cover dynamic programming, heaps, and binary search. Weeks 7-8 should focus on system design basics, mock interviews, and review. This sequencing ensures foundational skills before complex topics and builds up to realistic interview simulation.
Eight weeks is enough time to go from beginner to interview-ready for mid-level roles at most technology companies, provided you study consistently and strategically. The candidates who fail to improve despite months of preparation usually have one of three problems: they are reviewing solutions rather than solving problems, they are not practicing communication, or they are not reviewing their mistakes systematically. This guide provides a day-by-day structure and the meta-strategies that separate efficient preparation from wasted effort.
Before You Start: Setting the Right Foundation
Before beginning your study plan, establish three things.
Target company and role level. The preparation required for a junior role at a mid-size startup differs substantially from the preparation required for a senior role at a major technology company. Know what you are preparing for so you can calibrate the depth and topics accordingly.
Current baseline. Spend the first day solving five LeetCode Easy problems and two Medium problems without looking at solutions. This tells you where you are starting. Candidates who struggle with Easy problems need to begin at the fundamentals. Candidates who find Medium problems straightforward can skip some of the basic content.
Time budget. The study plan below assumes two to three hours per day. If you can only invest one hour, extend the plan to 14-16 weeks. If you can invest more, you can compress. Do not try to do 8 hours in a single day and then rest for two days — daily consistency is more effective for retention.
Week-by-Week Study Plan
Week 1: Arrays and Strings
Core topics: Array traversal, two-pointer technique, sliding window, prefix sums, string manipulation.
LeetCode problems to solve (Easy): Valid Palindrome, Valid Anagram, Two Sum, Best Time to Buy and Sell Stock, Contains Duplicate.
LeetCode problems to solve (Medium): Longest Substring Without Repeating Characters, 3Sum, Container With Most Water, Product of Array Except Self.
Daily structure: One hour of topic review, one hour of problem solving, 30 minutes of solution review and reflection.
Key milestone: By end of week 1, you should be able to solve array Easy problems cleanly and have started developing intuition for when to use two pointers vs. sliding window.
Week 2: Hash Maps and Linked Lists
Core topics: Hash map applications, frequency counting, complement patterns, linked list traversal, reversal, fast/slow pointers.
LeetCode problems: Group Anagrams, Top K Frequent Elements, Reverse Linked List, Linked List Cycle, Merge Two Sorted Lists, LRU Cache (implementation focus).
Key milestone: Comfortable implementing a linked list without looking anything up. Able to immediately identify hash map as the right structure for lookup-heavy problems.
Week 3: Trees and Binary Search
Core topics: Binary tree traversals (recursive and iterative), BST operations, tree construction and validation, binary search on sorted arrays.
LeetCode problems: Maximum Depth of Binary Tree, Invert Binary Tree, Validate Binary Search Tree, Lowest Common Ancestor of a BST, Binary Search, Search in Rotated Sorted Array, Find Minimum in Rotated Sorted Array.
"Tree problems build on each other. If you cannot implement inorder traversal cleanly, you cannot solve more complex tree problems. Be rigorous about getting the foundational traversals correct before moving on." — Software Engineer, preparing for FAANG interviews
Key milestone: All four tree traversal orders implemented correctly without reference.
Week 4: Graphs
Core topics: Graph representation, BFS, DFS, connected components, cycle detection, topological sort.
LeetCode problems: Number of Islands, Clone Graph, Course Schedule (cycle detection), Course Schedule II (topological sort), Pacific Atlantic Water Flow, Number of Connected Components.
Key milestone: Implementing BFS and DFS on both explicit graphs and grids from memory. Understanding when each traversal is appropriate.
Week 5: Dynamic Programming
Core topics: Memoization, tabulation, linear DP, 2D DP, knapsack patterns.
LeetCode problems: Climbing Stairs, House Robber, Coin Change, Longest Common Subsequence, Edit Distance, Unique Paths, Partition Equal Subset Sum.
This week is typically the hardest. Budget extra time for DP. Focus on the state definition and recurrence relation, not just memorizing solutions.
Key milestone: Able to define the DP state and recurrence for a new problem you have not seen before.
Week 6: Heaps, Intervals, and Advanced Patterns
Core topics: Heap operations, k-largest/smallest patterns, interval merging and insertion, monotonic stacks.
LeetCode problems: Kth Largest Element in an Array, Top K Frequent Elements (heap approach), Merge Intervals, Insert Interval, Daily Temperatures (monotonic stack), Largest Rectangle in Histogram.
Key milestone: Comfortable with Python's heapq module or Java's PriorityQueue for heap-based problems.
Week 7: Mock Interviews and Weak Area Review
Structure shift: This week should be mostly practice, not new learning.
Monday/Wednesday/Friday: Complete timed mock interviews using a platform like LeetCode, Pramp, or interviewing.io. Each mock should be 45-60 minutes with a partner or interviewer if possible.
Tuesday/Thursday/Saturday: Review your weak areas from the previous six weeks. Focus on the problem categories where your success rate is lowest.
Key milestone: Completing a medium LeetCode problem in under 25 minutes with clean code and correct complexity analysis.
Week 8: Company-Specific Preparation and Final Simulation
Spend the first half of the week:
- Reviewing the LeetCode company tag for your target company
- Solving problems from the company's reported question pool
- Re-solving problems from weeks 1-4 that you originally got wrong
Spend the second half of the week:
- Full-loop mock interviews (3-4 problems in sequence with breaks)
- Reviewing your systematic process (phases 1-5 from the coding problem framework)
- Preparing behavioral answers for the companies you are targeting
The Most Effective Daily Practice Structure
A two-hour daily session should be structured as follows.
| Segment | Duration | Activity |
|---|---|---|
| Warmup | 15 min | Re-solve one problem from the previous day from scratch |
| New problem (first attempt) | 30 min | Attempt new problem with no hints |
| Review if stuck or done | 15 min | If stuck: review hint or solution and understand it. If done: optimize. |
| New problem (second attempt) | 30 min | Attempt second problem |
| Error journal update | 15 min | Document mistakes, patterns, insights |
| Review previous errors | 15 min | Revisit 2-3 problems from your error journal |
Error Journaling: The Practice That Separates Top Performers
The most impactful practice that most candidates skip is maintaining a systematic error journal.
For every problem you get wrong or struggle with, record:
- The problem name and category
- The mistake you made (wrong data structure, off-by-one error, incorrect edge case handling, complexity misidentification)
- The correct approach
- The pattern to remember
Review your error journal entries at the start of each week. Re-solve the problems from your journal without looking at your notes.
"Reviewing solved problems feels productive but is not. The only productive thing is struggling with a problem you cannot solve. Your error journal is a record of exactly the problems you should be spending time on." — Software engineer, documenting interview preparation process
Tracking Progress: When You Are Ready
You are ready to start actual interviews when:
- You can solve at least 70% of LeetCode Medium problems in under 30 minutes
- You can articulate the time and space complexity of any solution you write
- You can implement BFS, DFS, binary search, and two-pointer from memory cleanly
- You have completed at least 5 timed mock interviews
- You can talk through your approach before coding without being prompted
| Metric | Not Ready | Getting Close | Ready |
|---|---|---|---|
| Easy solve rate | Below 80% | 80-90% | Over 90% |
| Medium solve rate | Below 40% | 40-60% | Over 60% |
| Medium solve time | Over 40 min | 30-40 min | Under 30 min |
| Mock interviews completed | 0-2 | 3-5 | 5+ |
| Error journal entries reviewed | Never | Sometimes | Weekly |
Frequently Asked Questions
Is 8 weeks enough to prepare for FAANG-level interviews? It depends heavily on your starting point and target level. For a junior role at a FAANG company, 8 weeks of consistent daily practice is borderline sufficient for a motivated candidate with existing programming experience. For a senior role, 12-16 weeks is more realistic. The 8-week plan is calibrated for mid-level roles at competitive companies.
How many LeetCode problems do I need to solve before I am ready? Quality matters more than quantity, but 150-200 problems of varied difficulty is a reasonable target for competitive roles. This should include approximately 40% Easy, 45% Medium, and 15% Hard problems. Focus on solving new problems independently before reviewing solutions rather than building a large count of reviewed solutions.
What should I do if I miss a day or fall behind? Do not try to catch up by doubling the next day's workload. Resume the plan from where you are. One missed day rarely has lasting impact. Trying to compensate with a marathon session often leads to burnout and poor retention. Consistency matters more than any single session.
References
- Gayle Laakmann McDowell. (2015). Cracking the Coding Interview (6th ed.). CareerCup.
- Aziz, A., Lee, T. H., & Prakash, A. (2018). Elements of Programming Interviews. CreateSpace.
- Karpathy, A. (2014). A Survival Guide to a PhD. Reflections on structured learning applicable to technical preparation.
- Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20-26.
- Kornell, N., & Bjork, R. A. (2008). Learning concepts and categories: Is spacing the enemy of induction? Psychological Science, 19(6), 585-592.