LeetCode 75 vs. Blind 75 (Curriculum Comparison)

LeetCode 75 is an official LeetCode study plan built around 75 interview problems; Blind 75 is a community-curated set of 75 commonly practiced questions. Both cover core coding patterns, but neither is a credential or proof of job readiness. Choose one to start, then judge progress by independent problem-solving, not by how many boxes you check.

A common complaint is that interview-prep lists look clear until you start: one problem takes an hour, a familiar pattern appears in a new form, and finishing 75 questions starts to feel like the goal. It is not. The useful goal is learning to solve problems you have not seen before.

I treat these lists as study plans, not career qualifications. The choice depends on how you prefer to study, your current skills, and the roles you want. Here is how to compare them and use either one well.

Curriculum overview and candidate fit

These are practice collections, not academic programs. Neither requires admission, awards course credit, or grants a professional credential. There is no accrediting-body standard for either list, and neither has a universally accepted completion test. Choose based on the study experience you need, not on the idea that one list carries more formal weight.

LeetCode describes its 75-question plan as an interview-preparation study plan and commonly frames it as a one-to-three-month plan. Blind 75 is a community-curated collection of 75 interview questions, associated with the Blind and Tech Interview Handbook ecosystem. It is not an official LeetCode plan or an accredited curriculum.

Both suit learners who can already write and debug basic code in one interview language. You should be comfortable with arrays, strings, hash maps, stacks, queues, and recursion. If those ideas are new, learn basic programming and data structures first; otherwise, the lists may test unfamiliar foundations more than interview problem-solving.

Takeaway: Choose LeetCode 75 for a structured plan in LeetCode, or Blind 75 for a compact community list. Do not start both at once.

Problem coverage, learning requirements, and completion criteria

Both collections practice common data structures and algorithms: ways to store data and steps for solving problems. You will see areas such as arrays and hash maps, strings, two pointers, trees, graphs, and dynamic programming. Topic labels can help organize practice, but success depends on applying a method to a new question, not recalling a label.

The sets are not exact duplicates, and neither should be treated as a full computer science course. Their problems give practice with recurring interview patterns, but they do not replace coursework or cover every skill a particular employer may assess. Compare the current lists against the topics you need rather than assuming one provides complete coverage.

A useful completion standard is more demanding than “I saw the solution.” For each problem, try to solve it without hints, explain why your method works, name edge cases, and state time and space complexity. Complexity describes how resource use changes as the input grows. If you needed a hint or reviewed a solution, record that honestly.

Use a simple progress record:

• Independent solve: You completed it without solution hints.
• Hint-assisted solve: You needed a clue to make progress.
• Reviewed solution: You read or watched a full solution before solving.
• Re-solve: You returned later and solved it again without help.

These labels separate practice exposure from retained skill. For example, recognizing a solution after reading it is not the same as building that solution from a blank page. Re-solving after a delay gives you better evidence of what you can recall and explain.

Takeaway: Count independent solves separately from reviewed solutions. A useful milestone is explaining the approach and complexity, not reaching problem 75.

Study execution, feedback, and learner experience

A steady routine helps you learn patterns without turning practice into a race. Work through one topic at a time at first, attempt each question before opening hints, then review mistakes. Once you know several patterns, mix topics so you must decide which method fits instead of following a list’s order.

Start by checking your language and data-structure basics. If you cannot write a loop, use a hash map, or debug a simple function with confidence, spend time on those skills before tackling the lists. This is a readiness check, not an entrance rule; it helps you avoid mistaking a basic skill gap for a failure at interview problems.

For each question:

1. Read and restate it. Identify the input, expected output, and constraints.
2. Try independently. Make a real attempt before using a hint. If stuck, write down what you tried.
3. Explain the plan. Describe the key idea and why it should work.
4. Check edge cases. Consider empty input, repeated values, or boundary cases where relevant.
5. Review the solution. Compare approaches, then note time and space complexity.
6. Return later. Re-solve missed or hint-assisted problems after a delay.
7. Mix and time practice. Use unfamiliar, mixed-topic questions to test recognition under interview-like limits.

There is no official number of minutes that makes a solve count, or a set number of correct answers that certifies readiness. As a planning target, try a representative mixed set under timed conditions and track how often you solve without hints, where you get stuck, and what errors recur. Use the results to guide your next study block.

A practical scenario: a student has solid coding basics but wants a guided interview plan. LeetCode 75 may be a convenient starting point because it is presented as a study plan within the platform. A career changer who has already built basic data-structure skills may prefer Blind 75 as a compact set to schedule independently. These are examples of fit, not outcome claims.

Takeaway: Keep one plan as your main route, but let your error log decide what to study next.

Interview readiness and career-outcome limits

Finishing either list is a study milestone, not proof that you will pass an interview or get a job. Neither list publishes independently verified placement rates or job guarantees. Interview performance also depends on the role, the employer’s process, communication, experience, and the questions asked. Use the lists as one part of preparation, then test your skills in broader settings.

A stronger check is whether you can solve a representative mixed set without relying on the order or titles of the questions. Explain your thinking out loud, ask clarifying questions, discuss complexity, and respond to follow-up changes. If a problem feels familiar, try a variation to check whether you understand the method or only remember one answer.

Then add preparation that matches the roles you are targeting:

• Review job descriptions and identify the skills they ask for.
• Practice employer-specific interview formats when reliable information is available.
• Prepare to discuss projects, your decisions, and what you learned.
• Include behavioral interview practice; add system design when it fits the role and level.
• Continue building relevant skills through coursework, projects, or work experience.

In career advising, I focus on evidence a candidate can demonstrate, not just completed activities. The same principle applies here: a finished checklist shows that you worked through a list. Independent solutions, clear explanations, and strong performance on unfamiliar problems offer better evidence of progress.

Conclusion: Pick one collection, build a consistent practice habit, and use delayed re-solves and mixed problems to check retention. Add targeted preparation for your role. Neither collection replaces CS foundations, employer-specific practice, or proof of skill.

Frequently asked questions

These answers clarify the main differences and how to use each set. There is no universal rule that makes one list best for every candidate, and neither list has a formal completion threshold. Use your starting skills, study preferences, and practice results to decide what to do next.

Is LeetCode 75 the same as Blind 75?
No. Both contain 75 interview problems, but they are separate collections with different problem selections and topic balances.

Which list should I do first?
Choose LeetCode 75 if you want its official study-plan format. Choose Blind 75 if you prefer a compact community-curated set. Start with one.

Are the questions identical?
No. The lists may cover similar patterns and may overlap, but they are not identical. Check their current versions for exact questions.

How long does LeetCode 75 take?
LeetCode commonly presents its plan as a one-to-three-month study plan. Your pace depends on your background and available study time.

How long does Blind 75 take?
There is no single required schedule. Set a pace that gives you time to attempt, review, and revisit problems.

Do I need to finish Blind 75 before applying for jobs?
No. The list is not a job-readiness requirement. Apply based on your wider skills and experience, and keep preparing for the roles you want.

Should beginners start with either list?
Only if they can write and debug basic code and use common data structures. Otherwise, build those foundations first.

Does completing either list guarantee an interview or job offer?
No. Neither offers a job guarantee or verified placement rate. List completion alone does not establish interview performance.

Should I do both lists?
Not at the start. Finish and review one, then use the other selectively to find new problems or practice areas you missed.

How do I know whether I have learned a problem?
Try it again later without hints. Explain the approach, edge cases, and complexity. Then test yourself on mixed or unfamiliar problems.

(This article was written by one of our staff writers, James Holloway. Visit our Meet the Team page.)