Search Results for "interview"
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Showing 34 open source projects for "interview"
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huihut interview
A summary of C/C++ technical interview basics
interview is a curated repository of technical interview questions, solutions, and explanations covering a wide range of topics in computer science and software engineering. It aims to help developers prepare for job interviews by providing sample problems in algorithms, data structures, system design, databases, and programming language intricacies, often with code snippets and discussion. -
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iOS Interview Questions
iOS interview questions
This repository collects a broad, categorized list of interview questions (with expected answers) that are commonly asked in iOS or Swift engineering interviews. Topics range from language fundamentals (memory management, ARC, value vs. reference types), to UIKit/SwiftUI, concurrency, Grand Central Dispatch, background execution, networking, design patterns, system frameworks, and architecture decisions. -
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Android Interview Questions
Your Cheat Sheet For Android Interview
...The content favors concise, practical answers that interviewers expect, helping candidates rehearse concepts and trade-offs rather than memorize trivia. It’s equally useful for brushing up before an interview and for leveling up day-to-day Android engineering knowledge. -
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Python Interview Bible
Curated set of interview notes, Q&A, and code snippets
Python-Interview-Bible is a curated set of interview notes, Q&A, and code snippets aimed at helping candidates prepare efficiently for Python roles. It organizes content by topic—language essentials, data structures, algorithms, concurrency, networking, and databases—so you can target weak areas quickly. The repository emphasizes clear explanations and compact examples that demonstrate correct usage and common pitfalls. -
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System Design Primer
Learn how to design large-scale systems
...It offers both theoretical foundations—such as scalability principles, the CAP theorem, and consistency models—and practical exercises, including real-world system design interview questions with sample solutions, diagrams, and code. The repository also contains study guides for short, medium, and long interview timelines, allowing learners to focus on both breadth and depth depending on their preparation needs. In addition, it includes flashcard decks designed to reinforce learning through spaced repetition, making it easier to retain key system design knowledge. -
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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
...Later in the curriculum, you move into topics like CloudFormation, CodeCommit/CodePipeline/CodeBuild/CodeDeploy, Terraform on AWS, CloudTrail and Config for compliance, Elastic Load Balancing, and cloud migration strategies. A full day is dedicated to “500 AWS interview questions and answers,” which makes this repo double as an interview prep resource as well as a skills builder. -
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LeetCode Master
About "Code Thoughts" LeetCode Practice Guide: 200 classic questions
leetcode-master is a comprehensive collection of LeetCode solutions written in C++ and organized as a structured learning path for coding interview preparation. The repository contains detailed explanations, categorized problem sets, and step-by-step reasoning behind solutions, making it an effective study companion for developers preparing for technical interviews. Problems are grouped by topic—such as arrays, linked lists, dynamic programming, greedy algorithms, and graph theory—so learners can focus on specific areas systematically. ... -
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SYSADMIN Test Questions
A collection of Linux Sysadmin Test Questions and Answers
...The format encourages quick drills: pick a topic, answer from memory, then compare against concise explanations. Many questions highlight real-world troubleshooting patterns rather than purely theoretical trivia, reflecting what admins face daily. As an interview prep resource, it helps candidates assess breadth and identify weak spots before deeper study. For teams, it doubles as a training checklist to standardize baseline knowledge across junior and mid-level engineers. -
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Hiring Without Whiteboards
Companies that don't have a broken hiring process
...It encourages a shift away from brainteasers, riddles, or puzzle-based interviews, which can create unnecessary barriers for candidates. The repository not only provides a resource for job seekers looking for fairer interview processes but also offers guidance for companies seeking to improve their hiring practices. With community contributions, it continues to grow as a reference for employers and applicants who value practical, respectful, & effective technical evaluation. -
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System Design
Learn how to design systems and prepare for system design interviews
This project is an open, course-style repository designed to help you learn system design from fundamentals through advanced, interview-ready thinking. It organizes core networking and distributed-systems concepts into a structured path, so you can build intuition before jumping into “design X” exercises. It covers the building blocks that show up in real architectures, such as DNS, load balancing, caching, CDNs, proxies, scalability and availability tradeoffs, and storage patterns, then connects those pieces to larger system goals. ... -
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Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
This repository collects concise flash cards that cover the core ideas of a traditional computer science curriculum with a focus on interview readiness. The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. Many cards point at canonical definitions or contrasts (e.g., stack vs. queue, BFS vs. ... -
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JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
javascript-algorithms is an open source repository by Oleksii Trekhleb that provides implementations of algorithms and data structures in JavaScript. Each algorithm includes explanations, complexity analysis, and references for further reading, making it both a coding resource and a study guide. The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand... -
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Jenkins-Zero-To-Hero
Install Jenkins and configure Docker
Jenkins-Zero-To-Hero is a hands-on learning repository that teaches Jenkins from scratch, starting with installation and moving all the way to building end-to-end CI/CD pipelines. The course is designed around running Jenkins on an AWS EC2 instance, guiding you through installing Java, configuring Jenkins, and exposing it safely via security group rules. From there, it covers installing plugins like Docker Pipeline, configuring Docker as an agent, and wiring up multi-stage and multi-agent... -
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Yangshun Lago
Data Structures and Algorithms library in TypeScript and JavaScript
...Because the code is idiomatic JavaScript, it also helps front-end engineers strengthen fundamentals without switching languages. The repository’s structure lets you browse topic by topic and compare trade-offs such as time versus space complexity. It’s a handy companion to interview prep lists: after reading a concept, you can open the matching Lago implementation and trace it line by line. -
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JavaScript Questions
A long list of (advanced) JavaScript questions, and their explanations
This repo is a popular collection of JavaScript questions with detailed, approachable explanations that help you understand why the language behaves the way it does. It covers tricky corners—hoisting, closures, coercion, event loop, prototypes, this binding, async/await, and more—through short prompts followed by illuminating answers. Explanations often include runnable snippets and step-through reasoning so you can replicate results locally. The content is curated to sharpen mental models... -
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Best-websites-a-programmer-should-visit
Some useful websites for programmers
...Rather than being a random bookmark dump, it organizes resources into practical categories such as algorithms, competitive programming, reading materials, podcasts, newsletters, interview prep, design, security, performance, and more. The list aims to reduce the “what should I learn next?” friction by pointing you to high-signal, time-tested tutorials, references, and tools. Because it spans beginner to advanced topics, you can use it as an on-ramp when starting out and as a roadmap for deeper specialization later. ... -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is... -
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javascript-algorithms
JavaScript implementations of computer science algorithms
...It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts. Because algorithms are implemented in a language (JavaScript) many developers use daily, the repo becomes especially useful for students, interview-preparation candidates, or anyone wanting to learn algorithmic thinking without switching languages. The code tends to be readable, structured, and adapted to JavaScript idioms, making it easier to follow for JS developers. -
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Scalable-Software-Architecture
Collection of tech talks, papers and web links on Distributed Systems
...The aim is to help readers study how large systems operate: how to scale them, how to handle latency, failure, load, concurrency, and how to structure software for maintainability at scale. Because many interview and real-world engineering problems revolve around system design now, this collection serves as both prep material and a reference bank for engineers evolving beyond code to architecture. It promotes reading original source material (papers and talks) rather than merely summary blog posts, thereby helping practitioners deepen their mental models. ... -
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Guide to Technical Interviews
Guided collection and roadmap for preparing technical interviews
This repository is a guided collection and roadmap for preparing technical interviews, covering the gamut from algorithmic challenges and data structures to system design and behavioral preparation. It consolidates resources like interview question lists, practice platforms, mock interview sites, and recommended books or blogs. For individuals targeting big-tech or rigorous interview processes, this acts as a structured study guide rather than a random list of links. The README breaks down preparation into categories — coding problems, system design, mock interview sites — so you can identify gap areas and allocate study time accordingly. ... -
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Machine Learning Cheat Sheet
Classical equations and diagrams in machine learning
...Each section is presented concisely, often with diagrams, formula snippets, and short explanatory notes to serve as quick reference for students, practitioners, or interview prep. The repository is ideal for those who want a compact, at-a-glance reminder of ML fundamentals without diving back into textbooks. Because the cheat sheet is meant to be portable and broadly useful, it is format-friendly (often in Markdown, PDF, or image formats) and easy to include in learning workflow or slides. -
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CyC2018.github.io
Personal knowledge site built with GitHub Pages
This is a personal knowledge site built with GitHub Pages, organizing computer science notes and study materials in a browsable format. It aggregates content across algorithms, data structures, networking, operating systems, databases, and interview preparation into a coherent index. The presentation emphasizes succinct explanations paired with diagrams, tables, or code snippets to speed recall. Because the site is generated from a repository, it benefits from issue tracking, pull requests, and version history, making it easy to update and maintain. The structure encourages incremental learning: you can dip into a topic, follow internal links, and return later with a clear sense of progress. ... -
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Mega Project List
List of practical projects that anyone can solve in any prog language
...The concept is simple but powerful: instead of just memorizing algorithms, you pick a project (for example “Binary to Decimal and Back Converter”), implement it in your favorite language, and gradually build a portfolio of varied programming tasks. The repository has been widely referenced as a go-to for developers looking for ideas to practice, build side-projects, or create interview-prep exercises. Each entry is described in plain language, often with optional “added complexity” suggestions. The repo encourages contributions: you can add new projects, or strip duplicate items, and you can choose any language to implement. -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
...The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. It serves both as a self-study path and as a warm-up bank for interview prep or coding katas.
