Every page on this site teaches one topic well, but nobody studies one topic at a time in isolation — you have a deadline, a target company, or a target rating, and a limited number of hours per week. This page turns the phases you’ve already read (or are about to read) into an actual schedule: an 8-week interview plan, a competitive-programming ladder, and a system for tracking what’s actually sticking.

What you’ll learn

• An 8-week interview prep plan mapping each week to specific phases on this site.
• A competitive-programming ladder from beginner to advanced, tied to Codeforces-style rating bands.
• How to use spaced repetition and a weak-area log instead of just grinding problems linearly.
• Rough problem-count targets by difficulty for interview readiness.
• How to structure mock interviews in your final two weeks.

An 8-week interview prep plan

This assumes roughly 8-12 hours a week. Compress it to 4-5 weeks if you’re already comfortable with Phases 1-4, or stretch it if you’re starting from zero.

A competitive-programming ladder

Codeforces rating bands (or the rough equivalent on any other judge) map reasonably well onto a progression through this site’s phases.

  graph LR
    N0["Phase 1: Foundations"] --> N1["Phase 2: Python for DSA and CP"]
    N1 --> N2["Phase 3: Core Data Structures"]
    N2 --> N3["Phase 4: Sorting and Searching"]
    N3 --> N4["Phase 5: Interview Patterns"]
    N4 --> N5["Phase 6: Dynamic Programming"]
    N5 --> N6["Phase 7: Graphs Advanced"]
    N6 --> N7["Phase 8: Advanced CP Topics"]
    N7 --> N8["Phase 10: Interview and Contest Strategy"]
    N8 --> N9["Phase 11: Problem Sets"]

Climbing the ladder doesn’t require finishing every phase before starting the next one — most competitors cycle back through earlier phases as gaps show up in harder problems, which is exactly what spaced repetition below is for.

Spaced repetition and tracking weak areas

Solving a problem once and moving on is the least efficient way to make a pattern stick. Instead:

• Log every problem you attempt: name, pattern/tag, difficulty, date, and whether you solved it independently, with a hint, or by reading the solution.
• Re-attempt problems you struggled with after about a week, and again after about a month, from scratch (no peeking at your old code) — if it’s still slow the second time, the pattern hasn’t stuck yet.
• Tag by pattern, not just by problem name, so you can see which patterns (from the Pattern Recognition Guide) keep showing up in your “struggled” column — that’s your actual weak-area list, and it’s more useful than a raw count of problems solved.
• A plain spreadsheet with columns for problem, pattern, difficulty, date, and outcome is enough — the tracking matters more than the tool.

Mock interviews

Reading about the seven-step framework is not the same as running it under time pressure with someone watching.

• Do 4-6 mock interviews in your final two weeks, ideally with a peer, a platform built for it, or even by recording yourself narrating a solve out loud.
• Alternate roles. Interviewing someone else sharpens your sense of what “good communication” actually looks like from the other side of the table.
• Time-box each mock to about 45 minutes, matching real onsite rounds, and force yourself to talk through every step of the framework even on problems you recognize instantly.
• Review afterward, not just the code — did you clarify first? Did you state the brute force before optimizing? Did you test your own code before being asked?

Recap

• An 8-week plan moving through Phases 1 through 8 (with a review week using this phase) covers the full interview syllabus at a sustainable pace.
• The competitive-programming ladder ties Codeforces-style rating bands directly to phases on this site — climb it by cycling back to close gaps, not by rushing forward.
• Log every problem by pattern and revisit struggles after a week and a month — spaced repetition beats one-and-done grinding.
• Aim for roughly 150-250 problems total, and close out prep with several timed mock interviews.

Next: Problem Sets — curated problem lists organized by pattern and difficulty, ready to plug straight into the plan above.