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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 fastest way to build that confidence is to learn from resources that have already helped thousands of engineers succeed.
In this article, we’ll explore the 10 most reliable GitHub repositories for tech interview preparation, covering coding interviews, system design, back-end and front-end roles, and even machine learning interviews. Each collection focuses on what actually makes a difference in interviews, from data structures and algorithms to scalable system design and real-world trading.
# GitHub repositories to speed up tech interviews
// 1. Josham/Coding-Interview-University
Coding Interview University A checklist-based, multi-month study plan for software engineering interviews, focusing on the core CS topics that matter most (data structures, algorithms, Big O, and problem practice). It started with the author’s personal roadmap and grew into a structured repo with resources, daily guidance, and a clear path to developing for companies like Google, Amazon, and Microsoft.
// 2. Donmartin/System Design Primer
System Design Primer is a structured, open-source guide to learning to design scalable systems and prepare for System Design Interviews. It organizes scattered “systems at scale” concepts into one place, with clear trade-offs (such as latency vs. throughput and consistency vs. availability), practical building blocks (CDNS, load balancing, caches, databases, queues), and spaced repetition with example solutions, diagrams, and their flashcards.
// 3. Yangshun/Tech Interview Handbook
Tech Interview Handbook is a free, tailored technical interview prep guide for busy engineers, created by the author of Blind 75/Grind 75. It covers the entire interview end-to-end, including coding interview best practices, curated problem lists and samples, algorithm cheat sheets, resume and practice preparation, and even front-end resources, written directly in the repo and written directly.
// 4. KDN251/Interview
The interview A comprehensive coding interview prep repo developed by Kevin Naughton Jr., trusted by tens of thousands of engineers. It combines clear explanations of basic data structures and algorithms with classification problem implementations, live coding practice, mock interview platforms, and learning resources, making it a practical, one-stop reference for preparing Fung-style interviews.
// 5. Ashishups 1/Awesome Latecode Resources
This Terrible Latecode DSA Resources The repository is a structured collection of high-quality content for mastering data structures, algorithms, and common latecode patterns. It focuses on pattern-based learning, core 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 effective coding interview preparation.
// 6. Building genesis/fearful reinforcement
This Scalable Systems Design Reading List An organized, structured library of articles, talks, books, and real-world case studies that describe how large-scale systems scale from thousands to billions of users. It’s structured around practical outcomes: assessing slow systems (scalability vs. performance), avoiding and recovering from outages (availability and stability), preparing for system design interviews (notes, architectures, diagrams), and even scaling an engineering org (hiring, management, culture).
// 7. Doppler Q/The dreaded interview question
Great interview Technical interview resources are a “meta-list”: rather than having a single question bank, it calls for many high-quality lists of interview questions on many topics. Its purpose is to help you quickly find interview questions for a specific stack or domain without having to hunt on the internet. The repo is no longer actively supported, so think of it as a large snapshot of links that are still useful, but may contain outdated/obsolete resources.
// 8. Chilrangelo/30 second interviews
30 seconds into the interview A community-driven collection of common interview questions with short, clear answers, designed for quick revision before an interview. It covers practical, frequently asked topics in JavaScript, React, HTML, CSS, Accessibility, Node, and security. Rather than an in-depth lesson, it emphasizes quick recall, real-world understanding, and confidence under interview pressure, making it ideal for last-minute preparation.
// 9. Arialdomartini/Backend Developer-Interview Question
Backend Developer Interview Questions A discussion-driven collection of open-ended questions covering back-end engineering, system design, databases, distributed systems, architecture, security, and team practices. It intentionally provides no answers, which encourages deeper technical conversations rather than rote responses. This resource is used to spark thoughtful dialogue and assess real-world reasoning, design tradeoffs, and engineering maturity rather than a checklist-style interview.
// 10. Khingach/Machine Learning-Interview
Minimum Viable Study Plan for Machine Learning Interview A Practical, “Focus on It” Roadmap for ML Engineer and Data Science Interviews It combines ML system design case studies (recommendation, feed ranking, advertising, search), core ML fundamentals (statistics, classical ML, deep learning), and interview pre-drill (SQL, where needed) pre-pre-drill (SQL, a bit of late code), all supported by readings, quizzes, and real interview stories.
# Final thoughts
If there’s one thing I’ve learned, it’s that good interview prep isn’t about gathering resources, it’s about consistently using the right people. These collections cover coding, backend fundamentals, system design, scalability, and machine learning in a way that truly reflects real interviews.
My advice is simple: do as many job-related mock interviews as possible. Learn the sample answers, understand the thinking behind them, and make it a habit to practice about 20 questions every day. When it comes time for the interview, your answers won’t feel memorized or forced, they’ll come naturally and with confidence.
Abid Ali Owan For centuries.@1abidaliawan) 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 Telecommunication Engineering. His vision is to create an AI product using graph neural networks for students with mental illness.