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Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data.
Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.
A data scientist is a professional who creates programming code and combines it with statistical knowledge to create insights from data.
JavaScript: JavaScript Fundamentals, JavaScript Inventor - JavaScript Language Designer: Brendan Eich of Netscape on December 4, 1995; JavaScript DevOps - JavaScript SRE, Cloud Native JavaScript (JavaScript on Kubernetes - JavaScript on AWS - JavaScript on Azure - JavaScript on GCP), JavaScript Microservices, JavaScript Containerization (JavaScript Docker - JavaScript on Docker Hub), Serverless JavaScript, JavaScript Data Science - JavaScript DataOps - JavaScript and Databases (JavaScript ORM), JavaScript ML - JavaScript DL, Functional JavaScript (1. JavaScript Immutability, 2. JavaScript Purity - JavaScript No Side-Effects, 3. JavaScript First-Class Functions - JavaScript Higher-Order Functions, JavaScript Lambdas - JavaScript Anonymous Functions - JavaScript Closures, JavaScript Lazy Evaluation, 4. JavaScript Recursion), Reactive JavaScript), JavaScript Concurrency (WebAssembly - WASM) - JavaScript Parallel Programming - Async JavaScript - JavaScript Async (JavaScript Await, JavaScript Promises, JavaScript Workers - Web Workers, Service Workers, Browser Main Thread), JavaScript Networking, JavaScript Security - JavaScript DevSecOps - JavaScript OAuth, JavaScript Memory Allocation (JavaScript Heap - JavaScript Stack - JavaScript Garbage Collection), JavaScript CI/CD - JavaScript Dependency Management - JavaScript DI - JavaScript IoC - JavaScript Build Pipeline, JavaScript Automation - JavaScript Scripting, JavaScript Package Managers (Cloud Monk's Package Manager Book), JavaScript Modules - JavaScript Packages (NPM and JavaScript, NVM and JavaScript, Yarn Package Manager and JavaScript), JavaScript Installation (JavaScript Windows - Chocolatey JavaScript, JavaScript macOS - Homebrew JavaScript, JavaScript on Linux), JavaScript Configuration, JavaScript Observability (JavaScript Monitoring, JavaScript Performance - JavaScript Logging), JavaScript Language Spec - JavaScript RFCs - JavaScript Roadmap, JavaScript Keywords, JavaScript Operators, JavaScript Functions, JavaScript Built-In Data Types, JavaScript Data Structures - JavaScript Algorithms, JavaScript Syntax, JavaScript OOP (1. JavaScript Encapsulation - 2. JavaScript Inheritance - 3. JavaScript Polymorphism - 4. JavaScript Abstraction), JavaScript Design Patterns - JavaScript Best Practices - JavaScript Style Guide - Clean JavaScript - JavaScript BDD, JavaScript Generics, JavaScript I/O, JavaScript Serialization - JavaScript Deserialization, JavaScript APIs, JavaScript REST - JavaScript JSON - JavaScript GraphQL, JavaScript gRPC, JavaScript on the Server (Node.js-Deno-Express.js), JavaScript Virtualization, JavaScript Development Tools: JavaScript SDK, JavaScript Compiler - JavaScript Transpiler - Babel and JavaScript, JavaScript Interpreter - JavaScript REPL, JavaScript IDEs (Visual Studio Code, JavaScript Visual Studio Code, Visual Studio, JetBrains WebStorm, JetBrains JavaScript), JavaScript Debugging (Chrome DevTools), JavaScript Linter, JavaScript Community - JavaScriptaceans - JavaScript User, JavaScript Standard Library (core-js) - JavaScript Libraries (React.js-Vue.js-htmx, jQuery) - JavaScript Frameworks (Angular), JavaScript Testing - JavaScript TDD (JavaScript TDD, Selenium, Jest, Mocha.js, Jasmine, Tape Testing (test harness), Supertest, React Testing Library, Enzyme.js React Testing, Angular TestBed), JavaScript History, JavaScript Research, JavaScript Topics, JavaScript Uses - List of JavaScript Software - Written in JavaScript - JavaScript Popularity, JavaScript Bibliography - Manning JavaScript Series- JavaScript Courses, JavaScript Glossary - JavaScript Official Glossary, TypeScript, Web Browser, Web Development, HTML-CSS, JavaScript GitHub, Awesome JavaScript, JavaScript Versions. (navbar_javascript - see also navbar_web_development, navbar_javascript_versions, navbar_javascript_standard_library, navbar_javascript_libraries, navbar_javascript_reserved_words, navbar_javascript_functional, navbar_javascript_concurrency, navbar_javascript async)
Data Science: Fundamentals of Data Science, DataOps, Big Data, Data Science IDEs (Jupyter Notebook, JetBrains DataGrip, Google Colab, JetBrains DataSpell, SQL Server Management Studio, MySQL Workbench, Oracle SQL Developer, SQLiteStudio), Data Science Tools (SQL, Apache Arrow, Pandas, NumPy, Dask, Spark, Kafka); Data Science Programming Languages (Python Data Science, NumPy Data Science, R Data Science, Java Data Science, C++ Data Science, MATLAB Data Science, Scala Data Science, Julia Data Science, Excel Data Science (Excel is the most popular "programming language") - Google Sheets, SAS Data Science, C# Data Science, Golang Data Science, JavaScript Data Science, Kotlin Data Science, Ruby Data Science, Rust Data Science, Swift Data Science, TypeScript Data Science, Bash Data Science); Databases, Data, Augmentation, Analysis, Analytics, Archaeology, Cleansing, Collection, Compression, Corruption, Curation, Degradation, Editing (EmEditor), Data engineering, ETL/ ELT ( Extract- Transform- Load), Farming, Format management, Fusion, Integration, Integrity, Lake, Library, Loss, Management, Migration, Mining, Pre-processing, Preservation, Protection (privacy), Recovery, Reduction, Retention, Quality, Science, Scraping, Scrubbing, Security, Stewardship, Storage, Validation, Warehouse, Wrangling/munging. ML-DL - MLOps. Data science history, Data Science Bibliography, Manning Data Science Series, Data science Glossary, Data science topics, Data science courses, Data science libraries, Data science frameworks, Data science GitHub, Data Science Awesome list. (navbar_datascience - see also navbar_python, navbar_numpy, navbar_data_engineering and navbar_database)
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