Coding Interview Prep for Beginners

Where beginners go wrong

The most common beginner mistake is opening a problem list, finding a medium difficulty problem, spending three hours on it without solving it, reading the solution, and concluding that coding interviews are impossibly hard.

Coding interviews are hard. They are not impossibly hard. The issue is sequence. You cannot attempt a medium difficulty binary search problem before you understand how binary search works, why the loop invariant matters, and what the off-by-one error looks like. Trying to learn those things simultaneously from a problem you cannot solve is an inefficient and demoralizing way to prep.

Beginners need a sequence, not a problem list.

Before you start: prerequisites

Before coding interview prep makes sense, you need a working foundation in one programming language. You should be able to write loops, define functions, use arrays and hash maps, and understand basic time complexity (what O(n) means and why it matters). You do not need advanced CS knowledge. You do need the ability to write code without looking up syntax.

If you are not there yet, that is the actual starting point. Coding interview prep built on top of shaky fundamentals is painful and slow. Two weeks of solidifying Python or JavaScript basics will save you months of confusion later.

The pattern-first roadmap

The right approach for beginners is to study algorithmic patterns in order of frequency and prerequisite dependency, then solve representative problems for each pattern, then drill recall. Here is the sequence.

Phase 1: Core patterns (weeks 1 to 3)

These four patterns appear in the largest number of interview problems and have the shortest prerequisite chains. Learn them first.

• Hash Maps. The most universally applicable tool in interview problems. Two Sum is the canonical example. Understand how lookup in O(1) time changes the solution space, and when to reach for a hash map instead of a nested loop.
• Two Pointers. A pattern for eliminating nested loops in sorted arrays and strings. The key concepts are pointer placement, when to advance each pointer, and what invariant the two pointers maintain.
• Sliding Window. An extension of two pointers for problems involving subarrays or substrings with a constraint. The critical skill is knowing when to shrink the window and what to track inside it.
• Binary Search. Appears far beyond the obvious sorted array case. Understand the loop invariant (what the left and right pointers represent at every step), not just the mechanics.

For each pattern: read the guide, write the template from memory, solve 3 representative problems, drill the specific lines you missed. Do not move on until you can produce the template without reference.

Phase 2: Intermediate patterns (weeks 4 to 6)

• Stacks. The data structure behind matching problems, next greater element, and expression evaluation. Understand when a stack tracks local context that later elements might resolve.
• BFS. The standard template for shortest paths and level order traversal. The key skill is recognizing when to use BFS over DFS and how to track visited nodes.
• DFS. Recursion on trees and graphs. The template is short. The skill is recognizing what to pass down and what to return up, and how to handle backtracking.
• Dynamic Programming. The hardest of the core patterns. Start with linear DP problems (Climbing Stairs, House Robber) before attempting 2D DP. The critical skill is defining the state and the transition, not the code itself.

Phase 3: Advanced patterns and mock interviews (weeks 7 to 10)

By Phase 3, you have solid recall on 8 patterns. Now add the less common but still important ones: Heaps, Backtracking, Merge Intervals, Tries. These appear in harder problems and in interviews at more demanding companies.

Also in Phase 3: start timed mock interviews. Not earlier. Mock interviews test whether you can apply knowledge under pressure. They require that you have solid knowledge to apply. Attempting mock interviews before your pattern recall is reliable just adds stress without useful signal.

Study habits that matter

Sequence matters, but so does how you study within that sequence:

• Always attempt retrieval before reviewing. Before opening a solution or guide, write what you can from memory. Even if it is mostly wrong, the attempt matters.
• Study in daily sessions of 1 to 2 hours rather than marathon weekend sessions. Spacing your practice is what builds long-term retention. Cramming builds short-term recognition that fades before the interview.
• Stop counting problems solved. The useful metric is: for each pattern, can you produce the template from memory in under two minutes and then apply it to a problem you have not seen before?
• Drill your weak lines specifically. If you always blank on the sliding window shrink condition, drill that line ten times. Do not re-read the entire solution.

The AlgoDrill pattern guides follow this sequence and connect explanation directly to recall drills. Start with Hash Maps or Two Pointers and work through the phase sequence. When you are ready to add recall practice on top of a pattern you have already learned elsewhere, the practice problems are organized by pattern for exactly that purpose.