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Data Structures & Algorithms Study Plan

Generate a personalized DSA study plan based on your timeline, weak areas, and target companies with daily problem sets.

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prompt.txt

                                

What this prompt does

This prompt builds a personalized DSA study plan from your situation. You provide your [timeline], [experience_level], [strong_areas], [weak_areas], and [target_companies], and the AI generates a weekly schedule at [hours_per_week], a prerequisite-ordered topic sequence, per-topic concept explanations with [problems_per_topic] curated problems easy-to-hard, the full [topics] list, a spaced-repetition schedule, weekly mock interviews starting week [mock_start], company-specific focus, progress checkpoints, per-topic resources, and a day-before review checklist in printable format.

The structure works because effective DSA prep is sequenced, not random. By ordering topics so prerequisites come first and weighting time toward your [weak_areas], the prompt avoids the common trap of grinding what you're already good at because it feels productive. Spaced repetition keeps solved problems from fading, which matters because a problem solved once in week one is usually forgotten by interview day without deliberate revisiting. Tying focus to [target_companies] aligns practice with the patterns those companies actually test, and gating mock interviews to start at week [mock_start] means you build a base before you stress-test it. The printable checklist format turns an abstract plan into something you can mark off daily, which is what keeps a multi-week effort from quietly stalling.

When to use it

  • You have a fixed [timeline] before interviews and need a structured plan, not a problem dump.
  • You know your [weak_areas] and want time weighted toward them.
  • You want topics ordered so prerequisites land before advanced material.
  • You need a spaced-repetition schedule so solved problems stick.
  • You are targeting specific [target_companies] and want their patterns prioritized.
  • You want a printable checklist to track progress and review the day before.

Example output

Expect a week-by-week schedule at [hours_per_week], a prerequisite-ordered topic list covering [topics], per-topic concept notes with [problems_per_topic] graded problems, a spaced-repetition revisit schedule, a mock-interview cadence from week [mock_start], checkpoints, resources per topic, and a printable day-before checklist — all framed as a trackable plan.

Pro tips

  • Be honest about [weak_areas]; the plan weights time toward them, so understating your gaps wastes the personalization.
  • Set [hours_per_week] to what you can truly sustain over the full [timeline] — an overcommitted schedule collapses in week two and the spaced repetition breaks.
  • Use the prerequisite ordering as written; jumping to dynamic programming before solid recursion and arrays usually means relearning fundamentals mid-stream.
  • Keep [problems_per_topic] manageable so you can actually solve and revisit them, rather than collecting unsolved problems.
  • Start mock interviews at [mock_start] even if you feel unready — performing under simulated pressure exposes gaps that solo solving hides.
  • Treat the spaced-repetition schedule as non-negotiable; revisiting solved problems is what converts short-term solutions into durable pattern recognition.
  • Lean on the company-specific focus for [target_companies], since each shop tends to favor particular topics and problem styles you can prepare for directly.

Frequently Asked Questions

Does it tailor the plan to my weak areas?
Yes. You provide `[strong_areas]` and `[weak_areas]`, and the plan weights time and problem selection toward the weak ones. Being honest about your gaps is what makes the personalization useful, since understating them produces a generic schedule.
Are the topics ordered by difficulty or prerequisites?
By prerequisites — the sequence builds so foundational topics like arrays and recursion come before dependent ones like dynamic programming and graphs. Following that order avoids hitting advanced material before you have the fundamentals it relies on.
Can it target specific companies?
Yes, via `[target_companies]`. The plan adds company-specific focus areas based on the interview patterns those companies are known for, so naming your real targets sharpens which topics and problem types get emphasized.
What if I can't commit the planned hours?
Set `[hours_per_week]` to what you can genuinely sustain across the whole `[timeline]`. An overcommitted schedule breaks down quickly and disrupts the spaced-repetition cadence, so a realistic, maintainable pace beats an ambitious one you abandon.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

Engr Mejba Ahmed

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