30 open-source projects similar to alexeygrigorev/data-science-interviews, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
This project is a comprehensive knowledge base and study resource designed for mastering technical interviews. It provides structured guides, roadmaps, and curricula focused on data structures, algorithms, system design, and frontend engineering to help candidates prepare for software engineering screenings. The repository distinguishes itself by offering a holistic approach to professional advancement. Beyond technical drills, it includes a career development handbook covering resume optimization, salary benchmarking, and strategic negotiation coaching. It also provides detailed methodologie
This project is a technical interview study guide and computer science knowledge base. It provides a curated collection of technical interview questions and expert explanations focused on preparing for assessments at global IT companies. The repository serves as a coding interview roadmap for mastering algorithmic challenges and complexity analysis, alongside a software architecture reference for design principles and system design strategies. It also includes a web security curriculum covering authentication methods, cryptographic concepts, and common vulnerabilities. Content covers compute
This repository serves as a structured educational resource for machine learning and data science, providing a centralized collection of tutorials, lecture notes, and implementation guides. It is designed to support self-directed learning by organizing complex technical concepts into a clear, hierarchical path that spans from foundational statistical methods to advanced deep learning architectures. The project distinguishes itself through a comprehensive approach to skill development, bridging the gap between theoretical algorithmic foundations and functional software applications. It offers
CS-Base is a comprehensive educational platform and technical repository designed to support software engineers in mastering backend architecture, artificial intelligence engineering, and career development. It functions as a centralized knowledge hub that combines illustrated theoretical tutorials with practical, project-based learning to bridge the gap between foundational computer science concepts and professional industry requirements. The project distinguishes itself by integrating a robust career mentorship framework with advanced AI engineering resources. It provides users with tools f
This repository serves as a comprehensive educational resource for machine learning, providing a structured collection of lecture notes and reference materials. It covers the fundamental mathematical and statistical principles required to build, evaluate, and optimize predictive models, ranging from basic probability and linear algebra to advanced algorithmic implementations. The content is organized through a hierarchical mapping of concepts that connects mathematical prerequisites to specific machine learning theories. It features a modular design that segments complex topics into discrete,
This project is a comprehensive educational roadmap designed to guide software engineers through the mastery of computer science fundamentals and technical interview preparation. It provides a structured, dependency-aware learning path that organizes complex computing concepts into a hierarchical curriculum, enabling users to build a professional engineering foundation through iterative study and practical implementation. The curriculum distinguishes itself by integrating theoretical knowledge with professional development, offering a unified index of cross-referenced resources including book
This project is a comprehensive study guide and knowledge base for deep learning, machine learning, and the associated mathematics required for artificial intelligence. It functions as a curated collection of technical questions and answers designed to help users study fundamental theories and practical applications. The repository serves as a technical interview preparation resource by aggregating industry-standard questions and core knowledge points. It provides a structured reference for reviewing neural network architectures and specific techniques used in computer vision, such as object
This project is a technical career guide and resource for developers navigating the software engineering job market. It serves as a comprehensive roadmap for securing professional employment, providing a technical interview preparation guide and a directory for mentorship and fellowships. The project provides a framework for drafting technical resumes and portfolios, focusing on describing project experience through metrics to attract recruiters. It also details professional networking strategies, including methods for executing cold outreach and securing job referrals. The resource covers b
This project is an open-source knowledge repository that serves as a comprehensive technical interview question bank for backend engineering roles. It provides a structured resource for hiring managers and candidates to evaluate proficiency in software design, architectural patterns, and core engineering principles through a curated collection of discussion topics and coding challenges. The repository functions as a programming paradigm evaluation tool, enabling the assessment of a candidate's understanding of object-oriented, functional, and procedural techniques. It distinguishes itself by
This project is a Linux system administration question bank designed to evaluate knowledge of server management. It serves as a technical reference and study guide through a collection of curated questions and answers. The resource provides targeted preparation for technical interviews and professional exams. It specifically covers DevOps interview preparation, including containerization, continuous integration, and version control. The knowledge base spans several core competency areas, including system internals, kernel architectures, and the Linux boot process. It also includes materials
This project is a comprehensive technical interview question repository designed to assist software engineers in their professional development. It serves as a structured study guide that aggregates curated questions and answers covering full-stack development, algorithmic challenges, and system design concepts. The resource distinguishes itself by organizing content into specialized technical domains, allowing candidates to focus their preparation on specific skill sets such as data science and machine learning. It provides a centralized library of architectural patterns and complex problem-
JavaHome is a backend engineering study resource and learning roadmap for Java developers. It provides a structured guide for mastering core language features and backend engineering best practices. The project serves as a technical interview preparation guide, featuring a collection of common interview questions and real-world exam samples. It focuses on developing professional skills in Java backend engineering, specifically targeting the ability to build scalable distributed systems. The material covers backend performance optimization, including the implementation of clean coding standar
This repository is a comprehensive resource for software engineering career development and technical interview preparation. It provides a structured collection of learning materials, algorithmic patterns, and system design guides designed to assist developers in mastering the core competencies required for professional engineering roles. The project distinguishes itself through a pattern-based content taxonomy that groups diverse technical challenges by underlying algorithmic strategies. This approach allows users to identify and apply reusable solutions during high-pressure assessments. It
This project is a collection of comprehensive guides and reference materials designed for technical interviews, machine learning system design, and professional development. It serves as a technical knowledge base and a career coaching manual, providing structured resources to help candidates navigate the machine learning hiring landscape. The resource distinguishes itself by offering detailed frameworks for comparing industry roles, analyzing company types, and planning long-term career progression. It provides specific guidance on evaluating employer organizational health, identifying resea
This project is an interactive learning platform designed to help users build proficiency in Python through a structured sequence of programming challenges. It functions as an online coding exercise environment where learners can practice syntax, data structures, and algorithmic logic directly within a web browser. The platform distinguishes itself by utilizing a WebAssembly-based runtime that executes Python code locally in the client. This approach provides an immediate feedback loop for script evaluation and logic testing without requiring the installation of local software or the configur
This repository is a collection of solved algorithmic problems and data structure exercises designed for technical interview preparation. It serves as a polyglot reference implementation, providing a set of solved exercises based on a standard textbook to help candidates master the logic and complexity analysis required for coding tests. The project implements the same algorithmic logic across multiple programming languages to demonstrate platform-independent problem solving. This polyglot approach allows for the comparison of implementations across different tech stacks to highlight recurrin
This project is a technical interview study guide and knowledge base designed for software engineering and AI roles. It provides curated learning paths and a collection of high-frequency questions to help candidates prepare for technical assessments. The resource includes specialized study guides for machine learning, covering supervised and unsupervised learning, computer vision, and natural language processing. It also serves as a system design reference, analyzing architectural patterns, scalability trade-offs, and distributed infrastructure components. Beyond technical theory, the projec
This repository is a structured database of coding interview problems designed to support software engineering career development. It functions as a centralized knowledge base that aggregates technical practice questions, mapping them to specific employer requirements and recurring computer science topics. The project distinguishes itself by clustering interview questions into company-specific collections and labeling them by technical domain. This organization allows users to identify recurring algorithmic patterns and analyze the unique testing styles associated with different organizations
This project is a curated collection of technical reference materials and study guides designed for machine learning interview preparation. It provides comprehensive resources for candidates pursuing engineering roles, focusing on deep learning, production infrastructure, and large-scale system design. The repository distinguishes itself through an architecture that combines theoretical research with industrial case studies. It utilizes a pattern-based approach to system design, breaking down complex deployments—such as recommendation engines, search ranking, and ad click prediction—into reus
HowToBeAProgrammer is a comprehensive software engineering career guide and professional development framework. It serves as a curated-knowledge repository and handbook designed to help programmers acquire technical habits and social competencies necessary for professional advancement. The project distinguishes itself by integrating technical craftsmanship with a detailed manual for technical leadership and organizational navigation. It provides specific strategies for career progression, such as compensation negotiation, promotion readiness, and the management of professional boundaries to p
This project is a frontend interview question bank and a comprehensive web development curriculum. It serves as a technical reference and study guide for software engineering candidates, combining a curated collection of interview questions and answers with a broad computer science fundamentals reference. The knowledge base is structured as a markdown-based system, using a folder-based taxonomy and directory hierarchy to organize technical topics. It employs a git-driven workflow to manage contributions and updates to the content, which is delivered as static documentation. The curriculum co
This project is a comprehensive reference library and preparation guide for Python technical interviews. It combines theoretical guides on computer science fundamentals and language runtime internals with practical implementation examples of algorithms and data structures. The repository serves as a curated knowledge base that maps theoretical interview questions to concrete code snippets. It provides technical analysis of Python language internals, including memory management, garbage collection, and the global interpreter lock, alongside a library of creational and structural software desig
This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and educational materials. It serves as a centralized knowledge base for developers and researchers, organizing tools and frameworks by their primary programming language and technical domain to simplify discovery across the artificial intelligence ecosystem. The collection distinguishes itself by providing a cross-language development index that spans diverse programming environments, including C, C++, Rust, Clojure, and Python. It covers a wide range of specialized capabilities, fr
This project is a structured repository of technical interview questions and professional development resources designed for software engineering career advancement. It serves as a comprehensive database of high-frequency assessment materials sourced from real-world candidate experiences at major global technology companies. The collection is organized into a hierarchical directory structure categorized by company names and technical domains to facilitate navigation. By utilizing plain text serialization and static markdown content, the project ensures that all interview data remains human-re
This project is a collection of interactive Python notebooks and educational resources designed for mastering data science, machine learning, and numerical computing. It provides a series of practical guides and tutorials covering deep learning, big data processing, and statistical analysis. The repository features specialized instructional suites for implementing classical machine learning algorithms, building deep learning model architectures, and managing AWS cloud infrastructure. It includes dedicated notebooks for data visualization and numerical computing exercises. The project covers
This project is a curated repository of specialized technical questions and assessment guides used to evaluate proficiency in core web technologies. It serves as a question bank and assessment guide for testing knowledge of browser APIs, CSS, JavaScript, and HTTP protocols. The repository provides a technical skill evaluation framework consisting of open-ended prompts. These are used for front-end candidate evaluation, standardizing technical hiring workflows, and facilitating interview preparation for web developers. The content is organized via a category-driven information architecture an
This project is a technical interview question bank and study resource designed for software engineering interviews focusing on JavaScript. It serves as a curated guide containing technical questions and coding challenges to test proficiency in the language and its runtime. The repository provides a structured collection of core programming concepts and problem solving exercises. It covers frontend technical training and coding interview practice through a series of curated problems and theoretical questions. The content is organized into a topic-categorized information hierarchy using markd
InterviewThis is a developer interview question bank and employer evaluation framework. It provides a curated collection of targeted questions and discovery prompts designed to help software engineers audit the technical and cultural environments of prospective employers. The project offers specialized guides for technical due diligence, including assessments of the technical stack, infrastructure, and quality assurance practices. It includes structured frameworks for evaluating engineering culture, development workflows, and operational health, such as on-call expectations and incident respo
This project is a LeetCode solution repository and algorithm implementation library. It serves as a technical interview study guide, providing a collection of solved programming problems and algorithmic implementations. The repository focuses on coding practice management and algorithm study workflows. It organizes curated coding questions and answers to assist in preparing for technical job evaluations and software engineering assessments. The content is managed through a git-based system using markdown documentation and a category-based directory structure. This allows for the organization
This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that