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# Introduction
Technical interviews are not about memorizing random questions. They are about demonstrating clear thinking, strong fundamentals and the ability to reason under pressure. The quickest way to build that confidence is to learn from resources that have already helped thousands of engineers succeed.
In this article, we will explore the 10 most trusted GitHub repositories for technical interview preparation, including coding interviews, system design, backend and frontend roles, and even machine learning interviews. Each repository focuses on what really matters in interviews, from data structures and algorithms to scalable system design and real-world tradeoffs.
# GitHub repository for Asing Tech Interviews
// 1.javasham/coding-interview-university
Coding Interview University is a checklist-based, multi-month study plan for software engineering interviews, focused on the core CS topics that matter most (data structures, algorithms, Big-O, and problem practice). It started as the author’s personal roadmap and evolved into a structured repo with resources, daily guidance, and a clear path to preparation for companies like Google, Amazon, and Microsoft.
// 2. donmartin/system-design-primer
System Design Primer Designing Scalable Systems is a structured, open-source guide for learning and preparing for systems design interviews. It organizes scattered “systems at scale” concepts in one place with clear trade-offs (like latency vs. throughput and consistency vs. availability), practical building blocks (CDN, load balancer, cache, databases, queues) and practical interview exercises with example solutions, diagrams, and Anki flashcards for interval iteration.
// 3. yangshun/tech-interview-handbook
tech interview book Created by the author of Blind 75/Grind 75, it’s a free, curated technical interview preparation guide for busy engineers. It covers the entire interview journey from start to finish, including coding interview best practices, curated problem lists and patterns, algorithm cheatsheets, resume and behavioral preparation, and even front-end resources, with most of the content written directly into the repo (not just links) and open for community contribution.
// 4. kdn251/interview
Interview is a comprehensive coding interview preparation repo created by Kevin Naughton Jr., trusted by thousands of engineers. It combines clear explanations of core data structures and algorithms with graded problem implementations, live coding exercises, a mock interview platform, and learning resources, making it a practical, all-in-one reference for FAANG-style interview preparation.
// 5. ashishps1/amazing-leetcode-resources
it Amazing Leetcode DSA Resources The repository is a structured collection of high-quality materials for mastering data structures, algorithms, and common Leetcode patterns. It focuses on pattern-based learning, fundamental concepts, curated problem lists like Blind 75 and Top Interview Sets, plus templates, articles, videos, books, and visual tools, making it a practical hub for efficient coding interview preparation.
// 6. Binhgueynas/Amazing-Scalability
it Scalable System Design Reading List A curated, well-organized library of articles, talks, books, and real-world case studies that explain how large-scale systems remain fast, reliable, and resilient as they grow from thousands to billions of users. It’s structured around practical outcomes: diagnosing slow systems (scalability vs. performance), preventing and recovering from outages (availability and stability), preparing for system design interviews (notes, architecture, diagrams), and even scaling the engineering organization (recruiting, management, culture).
// 7. dopplerhq/amazing-interview-questions
amazing interview is a “meta-list” of technical interview resources: rather than being a single question bank, it produces multiple high-quality lists of interview questions across a huge range of topics. Its purpose is to help you quickly find interview questions for a specific stack or domain without searching on the Internet. The repo is also marked as no longer actively supported, so think of it as a big snapshot of links that are still useful, but may contain old/outdated resources.
// 8. chalrangelo/30-second-interview
30 seconds of interview is a community-curated collection of common interview questions with short, clear answers, designed for fast revision before an interview. It focuses on practical, frequently asked topics in JavaScript, React, HTML, CSS, Accessibility, Node, and Security. Instead of in-depth tutorials, it emphasizes quick recall, real-world understanding and confidence under interview pressure, making it ideal for last-minute preparation.
// 9. arialdomartini/back-end-developer-interview-questions
Back-end developer interview questions is a discussion-driven collection of open-ended questions covering backend engineering, systems design, databases, distributed systems, architecture, security, and team practices. It intentionally gives no answers, encouraging deep technical conversations rather than rote answers. The resource is best used to foster thoughtful dialogue and assess real-world reasoning, design tradeoffs, and engineering maturity rather than through checklist-style interviews.
// 10. khangich/machine-learning-interview
Minimum Viable Study Plan for Machine Learning Interview Here’s a practical, “focus on what’s really visible” roadmap to ML engineer and data science interviews. It blends ML system design case studies (recommendation, feed ranking, ads, search), core ML fundamentals (statistics, classical ML, deep learning), and interview preparation exercises (SQL, a little Leetcode where necessary), all supported by curated readings, quizzes, and real interview stories.
# final thoughts
If there’s one thing I’ve learned, it’s that good interview preparation isn’t about gathering resources, it’s about using the right resources consistently. These repositories cover coding, backend fundamentals, system design, scalability, and machine learning in a way that truly reflects real interviews.
My advice is simple: take as many job-related mock interviews as possible. Learn sample answers, understand the thinking behind them and make a habit of practicing about 20 questions every day. When it comes time for the interview, your answers won’t seem memorized or forced, they will come naturally and with confidence.
abid ali awan (@1Abidaliyawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a master’s degree in technology management and a bachelor’s degree in telecommunications engineering. Their vision is to create AI products using graph neural networks for students struggling with mental illness.
