# Awesome-Python-Learning
Python Learning Library
## Contents
Jobs
Programming (learning)
Roadmaps
MOOC and courses
Video
Textbooks
Books
Games for Education
Online education (others)
IT-events
Training
Project examples for Junior
Puzzles
Developer’s Tools
Articles about Software Engineering
Jobs
- [15 App Ideas to Build and Level Up your Coding Skills]
- [15 вопросов по Python: как джуниору пройти собеседование]
- [15 задач на собеседовании для программиста]
- [16-річний програміст із Черкащини — про те, як 11-класником влаштувався на роботу зі зарплатнею майже $1000 | DOU]
- [5 советов по созданию вашего резюме]
- [50+ Data Structure and Algorithms Problems from Coding Interviews – DEV Community 👩💻👨💻]
- [53 Python Interview Questions and Answers – Towards Data Science]
- [hh.ua]
- [How to write a killer Software Engineering résumé – freeCodeCamp.org – Medium]
- [Job search, venture investing & new tech products | AngelList]
- [Python програмісти – Джин]
- [Top 100 Data Structure and Algorithm Interview Questions for Java Programmers | Java67]
- [Top 75 Programming Interview Questions Answers to Crack Any Coding Job Interview | Java67]
- [What I want (and don’t want) to see on your software engineering resume]
- [Вакансії | DOU]
- [Вастрик.Инсайд #39: Войти в айти. Нужен ли диплом? Как учиться новому? Как оставаться востребованным? Есть ли жизнь после 30?]
- [Вастрик.Инсайд #46: Краткий гайд о том, как нанимать нормальных людей]
- [Де, як і скільки: аналізуємо найм джуніорів у 2019 році | DOU]
- [Как должно выглядеть резюме ИТ-специалиста: типичные ошибки глазами HR]
- [Как успешно пройти любое техническое собеседование]
- [Работа]
Programming (learning)
Roadmaps
- [My Data Science & Machine Learning, Beginner’s Learning Path | LinkedIn]
- [AI & ML дайджест #17: курсы по ML & DL, обзор популярных GAN архитектур, AI бот для ребенка | DOU]
- [Data Science Career Guide — Dataquest]
- [Data Science Career Tips Archives — Dataquest]
- [Full-Stack JavaScript in Six Weeks: A Curriculum Guide]
- [Grow]
- [Grow]
- [How to become a data scientist? – Towards Data Science]
- [How we built our first full-stack JavaScript web app in three weeks]
- [If I had to start learning Data Science again, how would I do it?]
- [omreps/programmer-competency-matrix: ENG -> RU: Матрица компетентности программиста, мой перевод]
- [Pandas Урок — чтение файлов csv, создание dataframe и фильтрация данных]
- [Programmer Competency Matrix — Sijin Joseph]
- [programmer-competency-matrix/partII.md at master · omreps/programmer-competency-matrix]
- [Python Developers Survey 2019 Results | JetBrains: Developer Tools for Professionals and Teams]
- [Quiz: Data Engineer, Data Analyst, Data Scientist — Which Role Fits You?]
- [Resources I Wish I Knew When I Started Out With Data Science]
- [Roadmap • mlcourse.ai]
- [Top 10 In-Demand programming languages to learn in 2020]
- [Warning: Your programming career – SoloLearn – Medium]
- [Дайджест материалов по трудоустройству в сфере IT]
- [Детальный план самообразования в Computer Science за 1.5 года]
- [Мапа розвитку в Data Science, або Як стати дослідником даних | DOU]
- [Программирование на Python: от новичка до профессионала]
- [Путь Python Junior-а в 2017]
- [Развивать себя]
- [Советы сеньоров: как прокачать знания junior Front-end/JavaScript | DOU]
- [Хочу стать веб-разработчиком: подробный план по изучению JavaScript]
MOOC and courses
- [[UNИX][Python-Dev] Лекция 1. Разработка ПО. Индивидуальное использование GIT – YouTube]
- [11.1 – Regular Expressions – Мичиганский университет | Coursera]
- [200+ SQL Interview Questions and Answers for Developers | Udemy]
- [6.006: Introduction to Algorithms – Massachusetts Institute of Technology]
- [Advanced Operating Systems]
- [AI For Everyone — главная | Coursera]
- [Algorithmic Toolbox | Coursera]
- [Amazon Web Services Sign-In]
- [An Introduction to Interactive Programming in Python (Part 1) – Rice University | Coursera]
- [An Introduction to Interactive Programming in Python (Part 1) — главная | Coursera]
- [AP®︎ Computer Science Principles (AP®︎ CSP) | Khan Academy]
- [App Maker Academy | LEARN]
- [Applied Machine Learning in Python — главная | Coursera]
- [Applied Machine Learning in Python | Coursera]
- [Applied Plotting, Charting & Data Representation in Python | Coursera]
- [Applied Plotting, Charting & Data Representation in Python | Coursera]
- [Applied Social Network Analysis in Python | Coursera]
- [Applied Text Mining in Python | Coursera]
- [Applied Text Mining in Python | Coursera]
- [Artificial Intelligence]
- [Artificial Intelligence for Robotics | Udacity]
- [Basics of Software Architecture & Design Patterns in Java | Udemy]
- [Become a Python Developer]
- [Become a Solution Architect: Architecture Course | Udemy]
- [Big Data Analytics in Healthcare]
- [Bootcamp – Scrimba Tutorial]
- [Bootstrap 4 Tutorial – Learn Bootstrap For Free | Scrimba]
- [Break Away: Programming And Coding Interviews | Udemy]
- [Caesar – CS50x]
- [Chat with React – Scrimba Tutorial]
- [Clean Code | LEARN]
- [Client-Server Communication]
- [Code Basics: основы программирования]
- [Codecademy]
- [CodeSkulptor]
- [Coding for Kids | Tynker]
- [Coding Interview Bootcamp Algorithms, Data Structures Course | Udemy]
- [Command Line Essentials: Git Bash for Windows | Udemy]
- [Computability, Complexity & Algorithms]
- [Computability, Complexity & Algorithms – Udacity]
- [Computer programming | Computing | Khan Academy]
- [Computer science | Computing | Khan Academy]
- [Continuous Integration and Continuous Delivery using Interactive Browser-Based Labs | Katacoda]
- [Continuous Integration with Jenkins | LEARN]
- [Convolutional Neural Networks | Coursera]
- [Course | 15.071x | edX]
- [Course | CS1301xII | edX]
- [Course Introduction: Neural Networks in JavaScript – Scrimba Tutorial]
- [Course overview]
- [Course Overview – Scrimba Tutorial]
- [Courses | edX]
- [Courses | LEARN]
- [Crash Course on Python — главная | Coursera]
- [CS 436: Distributed Computer Systems – Lecture 1 – YouTube]
- [CSS – Scrimba Tutorial]
- [Dashboard | Khan Academy]
- [Data Analysis and Visualization]
- [Data Analysis Learning Path | Springboard]
- [Data Science A-Z™: Real-Life Data Science Exercises Included | Udemy]
- [Data Science Dream Job – YouTube]
- [Data Science Interview Prep]
- [Data Science Office Hours – YouTube]
- [Data Science with R | Pluralsight]
- [Data Scientist Path: Interactive Python, SQL | Dataquest]
- [Data Structure – Part I | Udemy]
- [Data Structures and Performance | Coursera]
- [Data Structures Fundamentals]
- [Data Visualization in Python — DataCamp]
- [Data Wrangling with MongoDB]
- [Database Systems Concepts & Design]
- [DataCamp]
- [Datatypes & Typecasting – Scrimba Tutorial]
- [DBA1 : Компания Postgres Professional]
- [DBA2 : Компания Postgres Professional]
- [Deep learning на пальцах!]
- [Design of Computer Programs]
- [Design of Computer Programs – Udacity]
- [Designing RESTful APIs]
- [Developing AI Applications on Azure — главная | Coursera]
- [Differential Equations in Action]
- [Divide and Conquer, Sorting and Searching, and Randomized Algorithms | Coursera]
- [DJANGO CHANNELS 2 Tutorial (V2) – Real Time – WebSockets – Async – YouTube]
- [Docker Swarm Mode Playground | Katacoda]
- [DZone: Programming & DevOps news, tutorials & tools]
- [Easy to Advanced Data Structures | Udemy]
- [Easy to Advanced Data Structures | Udemy]
- [Exercise files]
- [Exercises on the Python Track | Exercism]
- [Explore – LeetCode]
- [Free Clean Architecture Course: Patterns, Practices, and Principles for Beginners | Pluralsight]
- [Free Software Architect Course: Developer to Architect | Pluralsight]
- [Free SOLID Course: Principles of Object Oriented Design | Pluralsight]
- [Front Matter — Alembic 1.4.2 documentation]
- [Front-End Web UI Frameworks and Tools: Bootstrap 4 — главная | Coursera]
- [Full Stack Foundations]
- [Git Playground | Katacoda]
- [Git Started with GitHub | Udemy]
- [Graph Search, Shortest Paths, and Data Structures — главная | Coursera]
- [Graph Search, Shortest Paths, and Data Structures | Coursera]
- [Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming | Coursera]
- [Grok Learning]
- [Grokking the System Design Interview – Learn Interactively]
- [GT – Refresher – Advanced OS]
- [Harvard CS109 Data Science Course, Resources Free and Online]
- [High Performance Computer Architecture]
- [High Performance Computing]
- [HTTP & Web Servers]
- [HTTP & Web Servers – Udacity]
- [https://scratch.mit.edu/projects/374672500/editor]
- [Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization | Coursera]
- [Inferential Statistical Analysis with Python — главная | Coursera]
- [Input and output — Intro to Interviewing — Grasshopper]
- [Intel® Edge AI Fundamentals with OpenVINO™]
- [Intro to Algorithms – Udacity]
- [Intro to Algorithms | Udacity]
- [Intro to Artificial Intelligence – Udacity]
- [Intro to Backend – Udacity]
- [Intro to Data Analysis | Udacity]
- [Intro to Data Science]
- [Intro to Data Science]
- [Intro to Data Structures and Algorithms]
- [Intro to Deep Learning with PyTorch]
- [Intro to Descriptive Statistics]
- [Intro to DevOps]
- [Intro To Dynamic Programming – Coding Interview Preparation | Udemy]
- [Intro To Dynamic Programming – Coding Interview Preparation | Udemy]
- [Intro to Flask Series – YouTube]
- [Intro to Hadoop and MapReduce]
- [Intro to Inferential Statistics]
- [Intro to Progressive Web Apps]
- [Intro to Relational Databases]
- [Intro to the Design of Everyday Things]
- [Intro to Theoretical Computer Science]
- [Introduction – Scrimba Tutorial]
- [Introduction to Computational Thinking and Data Science | edX]
- [Introduction to Computer Vision]
- [Introduction to D3 – Scrimba Tutorial]
- [Introduction to Data Science in Python | Coursera]
- [Introduction to Data Science in Python | Coursera]
- [Introduction to Dynamical Systems and Chaos]
- [Introduction to Graduate Algorithms]
- [Introduction to GraphQL | GraphQL]
- [Introduction to JavaScript | Codecademy]
- [Introduction to Machine Learning – Online Course | DataCamp]
- [Introduction to Machine Learning Course | Udacity]
- [Introduction to Operating Systems]
- [Introduction to Operating Systems – Udacity]
- [Introduction to Python Programming – Udacity]
- [Introduction to Python Programming | Udacity]
- [Introduction To Python Programming | Udemy]
- [Introduction to Scripting in Python | Coursera]
- [IT Курсы программирования онлайн – обучение программированию, видео уроки | ITVDN]
- [JavaScript ES6 Intro – Scrimba Tutorial]
- [Kaggle Mercedes и кросс-валидация / Блог компании Open Data Science / Хабр]
- [Katacoda – Interactive Learning Platform for Software Engineers]
- [Katacoda – Interactive Learning Platform for Software Engineers]
- [Khan Academy | Free Online Courses, Lessons & Practice]
- [Knowledge-Based AI: Cognitive Systems]
- [Learn | freeCodeCamp.org]
- [Learn CI/CD with Jenkins using Interactive Browser-Based Labs | Katacoda]
- [Learn CSS Animations]
- [Learn Data Analysis using Pandas and Python (Module 2/3) | Udemy]
- [Learn Data Structures and Algorithms: Ace the Coding Interview | Udemy]
- [Learn Data Visualization Tutorials | Kaggle]
- [Learn Git Version Control using Interactive Browser-Based Labs | Katacoda]
- [Learn How to Code | Codecademy]
- [Learn Intermediate Machine Learning Tutorials | Kaggle]
- [Learn Intro to Machine Learning Tutorials | Kaggle]
- [Learn Kubernetes using Interactive Browser-Based Labs | Katacoda]
- [Learn Machine Learning using Interactive Browser-Based Labs | Katacoda]
- [Learn Pandas Tutorials | Kaggle]
- [Learn Python – Full Course for Beginners [Tutorial] – YouTube]
- [Learn Python 3.6 for Total Beginners | Udemy]
- [Learn Python for Data Science, Structures, Algorithms, Interviews | Udemy]
- [Learn Python for Data Structures, Algorithms & Interviews | Udemy]
- [Learn Python: Build a Virtual Assistant | Udemy]
- [Learn Serverless and Functions/FaaS Technologies using Interactive Browser-Based Labs | Katacoda]
- [Learn SQL | Codecademy]
- [Learn to Code with Interactive Tutorials | Scrimba]
- [Learn to Program: Crafting Quality Code — главная | Coursera]
- [Learn to Program: The Fundamentals — главная | Coursera]
- [Lecture 1: Administrivia; Introduction; Analysis of Algorithms, Insertion Sort, Mergesort | Video Lectures | Introduction to Algorithms (SMA 5503) | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Linear Algebra Refresher Course]
- [Livestreams | Codecademy]
- [Machine Learning]
- [Machine Learning A-Z (Python & R in Data Science Course) | Udemy]
- [Machine Learning Course Outline | Course Outline | CSMM.102x Courseware | edX]
- [Machine Learning Foundations: A Case Study Approach | Coursera]
- [Machine Learning in Python (Data Science and Deep Learning) | Udemy]
- [Machine Learning Interview Preparation]
- [Machine Learning with TensorFlow on Google Cloud Platform | Coursera]
- [Machine Learning: Unsupervised Learning]
- [Master Object Oriented Programming Concepts | Udemy]
- [Master Python for Data Science]
- [Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Microsoft: Our new free Python programming language courses are for novice AI developers | ZDNet]
- [MIT 6.042J Mathematics for Computer Science]
- [Neural Networks and Deep Learning — главная | Coursera]
- [Node.js Playground | Katacoda]
- [Nonlinear Dynamics: Mathematical and Computational Approaches]
- [Open Data Science (ODS.ai)]
- [Open Data Science (ODS.ai)]
- [Open Machine Learning Course mlcourse.ai • mlcourse.ai]
- [ossu/computer-science: Path to a free self-taught education in Computer Science!]
- [Practical Deep Learning for Coders, v3 | fast.ai course v3]
- [Probabilistic Graphical Models 1: Representation | Coursera]
- [Programming Languages]
- [PY4E – Python for Everybody]
- [Python – OOP | Udemy]
- [Python – YouTube]
- [Python | CoderNet]
- [Python 3, BBC Microbit, and MicroPython Bootcamp | Udemy]
- [Python 3.4 Programming Tutorials – YouTube]
- [Python Basics — главная | Coursera]
- [Python for Big Data Analytics – Edureka]
- [Python for Data Science | edX]
- [Python for Data Science | edX]
- [Python OOP : Four Pillars of OOP in Python 3 for Beginners | Udemy]
- [Python OOP : Four Pillars of OOP in Python 3 for Beginners | Udemy]
- [Python Playground | Katacoda]
- [Python Programming – Build a Reconnaissance Scanner | Udemy]
- [Python Programming – YouTube]
- [Python Programming for Beginners – Learn in 100 Easy Steps | Udemy]
- [Python Programming: A Concise Introduction — главная | Coursera]
- [Python Track | Exercism]
- [Python Tutorials – YouTube]
- [Python Variables]
- [Python: Object Oriented Programming | Udemy]
- [python: Online Courses, Training and Tutorials on LinkedIn Learning]
- [Quickstart for Cloud SQL for PostgreSQL | Google Cloud]
- [R Language Playground | Katacoda]
- [React – Scrimba Tutorial]
- [React & Django TUTORIAL Integration // REACTify Django – YouTube]
- [React Tutorial: Learn React JS For Free | Scrimba]
- [Reading: Welcome | Welcome | ALGS201x Courseware | edX]
- [Real-Time Analytics with Apache Storm]
- [Regular Expressions Intro – Scrimba Tutorial]
- [Responsive Images]
- [Rock Paper Scissors – Python Tutorial | Udemy]
- [RPA: Automation Anywhere: Example: Ticket Processing – YouTube]
- [Scalable Microservices with Kubernetes]
- [Scipy Lecture Notes — Scipy lecture notes]
- [Self-Driving Fundamentals: Featuring Apollo]
- [Sequence Models | Coursera]
- [Shortest Paths Revisited, NP-Complete Problems and What To Do About Them | Coursera]
- [Software Architecture & Design]
- [Software Development Methodologies | LEARN]
- [Software Development Processes and Methodologies | Coursera]
- [Software Testing Introduction (RUS) | LEARN]
- [Spark]
- [SQL for Data Analysis | Udacity]
- [Stanford Engineering Everywhere | CS229 – Machine Learning]
- [Story by Data – YouTube]
- [Structuring Machine Learning Projects | Coursera]
- [TensorFlow Getting Started using Interactive Browser-Based Labs | Katacoda]
- [Textbook | Calculus Online Textbook | MIT OpenCourseWare]
- [The Bits and Bytes of Computer Networking | Coursera]
- [The Ultimate GIT 5-day Challenge | Udemy]
- [Tick Tock, Tick Tock — Етап 9 — Stepik]
- [Top Coding Interview Questions (Essential to Getting Hired) | Udemy]
- [Try Django 1.11 // Python Web Development | Udemy]
- [Try DJANGO Tutorial Series – YouTube]
- [Try DJANGO TUTORIAL Series (v2.2) // PYTHON Web Development with Django version 2.2 – YouTube]
- [TypeScript: Introduction – Scrimba Tutorial]
- [Ubuntu Playground | Katacoda]
- [UI design – Scrimba Tutorial]
- [Using Databases with Python | Coursera]
- [Version Control with Git]
- [Video | Version control with Git | VCG Courseware | LEARN]
- [Video Lectures | Introduction to Algorithms (SMA 5503) | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Video Lectures | Introduction to Computer Science and Programming | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Video Lectures | Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Visual Studio Code Playground | vscode | Katacoda]
- [Web Application & Software Architecture 101 – Learn Interactively]
- [Web Design, Business, Technology Classes and Immersives | General Assembly]
- [Web Tooling & Automation]
- [WebDriver | LEARN]
- [Web-Services Introduction | LEARN]
- [Website Performance Optimization]
- [Week 2 | Week 2 | CS50 Courseware | edX]
- [Welcome 👋 to Vue.js! – Scrimba Tutorial]
- [Алгоритмы | Coursera]
- [Алгоритмы на Python 3. Лекция №1 – YouTube]
- [Алгоритмы, часть I | Coursera]
- [Алгоритмы, часть I | Coursera]
- [Алгоритмы, часть II | Coursera]
- [Алгоритмы, часть II | Coursera]
- [Алексей Савватеев ” Математический анализ. Анонс” – YouTube]
- [Аналіз даних та статистичне виведення на мові R | Prometheus]
- [Бесплатное учебное руководство по теме “NumPy” — Deep Learning Prerequisites: The Numpy Stack in Python | Udemy]
- [Бесплатное учебное руководство по теме “Python” — Learn Python 3.6 for Total Beginners | Udemy]
- [Введение в математическое мышление | Coursera]
- [Введение в математическое мышление | Coursera]
- [Введение в науку о данных | Coursera]
- [Введение в программирование с MATLAB | Coursera]
- [Візуалізація даних | Prometheus]
- [Высшая математика для заочников и не только]
- [Глубокое обучение | Coursera]
- [Глубокое обучение | Coursera]
- [Интерактивные курсы — HTML Academy]
- [Інформація про курс CS50 | Prometheus]
- [Ключевые аспекты разработки на Python – Курсы по программированию]
- [Корисні ресурси для програміста (оновив 11 травня 2020) | DOU]
- [Курсы по программированию]
- [Машинне навчання | Prometheus]
- [Машинное обучение | Coursera]
- [Машинное обучение | Coursera]
- [Машинное обучение | Coursera]
- [Машинное обучение для людей :: Разбираемся простыми словами :: Блог Вастрик.ру]
- [Начало]
- [Нейронные сети и глубокое обучение | Coursera]
- [Онлайн-курсы — когда угодно, где угодно | Udemy]
- [Онлайн-курсы Computer Science Center]
- [Основи програмування CS50 2019 | Prometheus]
- [Основы React.js]
- [Основы компьютерных вычислений | Coursera]
- [Открытый курс машинного обучения. Тема 1. Первичный анализ данных с Pandas / Блог компании Open Data Science / Хабр]
- [Открытый курс машинного обучения. Тема 2: Визуализация данных c Python / Блог компании Open Data Science / Хабр]
- [Открытый курс машинного обучения. Тема 3. Классификация, деревья решений и метод ближайших соседей / Open Data Science corporate blog / Habr]
- [Открытый курс машинного обучения. Тема 3. Классификация, деревья решений и метод ближайших соседей / Блог компании Open Data Science / Хабр]
- [Панель курсів | Prometheus]
- [Практическое компьютерное обучение | Coursera]
- [Прикладная наука о данных с Python | Coursera]
- [Программирование мобильных приложений для портативных систем на базе Android: Часть 1 | Coursera]
- [Программирование мобильных приложений для портативных систем на базе Android: Часть 2 | Coursera]
- [Программирование на Python | Coursera]
- [Профессиональная сертификация ‘Google IT Automation with Python’ | Coursera]
- [Разведочный анализ данных | Coursera]
- [Разработка и проектирование адаптивных веб-сайтов | Coursera]
- [Розробка та аналіз алгоритмів. Частина 1 | Prometheus]
- [Скринкаст по Angular]
- [Скринкаст по Gulp]
- [Скринкаст по Node.JS]
- [Скринкаст по Webpack]
- [Современный учебник JavaScript]
- [Структуры данных в Python | Coursera]
- [Структуры и алгоритмы данных | Coursera]
- [Теория вероятностей для начинающих | Coursera]
- [Теория игр | Coursera]
- [Уроки по Python для начинающих и программистов ~ PythonRu]
- [Учимся программировать: основы | Coursera]
- [Функции – Московский физико-технический институт, Mail.Ru Group & ФРОО | Coursera]
- [Язык программирования JavaScript]
- [🤖 Интерактивные эксперименты с машинным обучением на TensorFlow | DOU]
Video
- [6.824 Lecture 1 – YouTube]
- [62 лучших видео для тех, кто хочет углубить знания в JavaScript]
- [AlSweigart – Twitch]
- [Berkeley AI Materials]
- [Build a Data Analysis Library from Scratch in Python – YouTube]
- [Building a keylogger using Python + Pynput – YouTube]
- [Compilers with Alex Aiken – YouTube]
- [Computer Science 162 (Fall 2010) – Lecture 1 – YouTube]
- [Computer Science 61A, 001 – Spring 2011 : Free Movies : Free Download, Borrow and Streaming : Internet Archive]
- [CS144 Fall 2013, Video 4-0: Congestion Control – YouTube]
- [Essence of linear algebra – YouTube]
- [Git – Lecture 0 – CS50’s Web Programming with Python and JavaScript – YouTube]
- [Golovach Courses – YouTube]
- [L01 Functional Programming | UC Berkeley CS 61A, Spring 2010 – YouTube]
- [Steven Skiena – Algorithms]
- [Tech Debates Webinar | Ruby vs Python – Zoom]
- [UC Berkeley CS professor Brian Harvey]
- [UCBerkeley Course Computer Science 186 : Free Download, Borrow, and Streaming : Internet Archive]
- [Video Lectures | Structure and Interpretation of Computer Programs | Electrical Engineering and Computer Science | MIT OpenCourseWare]
- [Изучение программирования. SQL – YouTube]
- [Лучшие Youtube-каналы для Frontend-разработчика]
- [Лучший видеокурс по сетевым технологиям]
- [Огромный видеокурс по основам JavaScript от freeCodeCamp]
Textbooks
- [100 days of algorithms — Medium]
- [30 Helpful Python Snippets That You Can Learn in 30 Seconds or Less]
- [97-things-every-programmer-should-know/ru/thing_01 at master · 97-things/97-things-every-programmer-should-know]
- [All the basics of Python classes – Level Up Coding]
- [BeginnersGuide/Programmers – Python Wiki]
- [Calculating Streaks in Pandas]
- [Cheat Sheet – Google Таблиці]
- [Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets]
- [Deep Learning]
- [DevDocs API Documentation]
- [DZone Big Data]
- [Front-end Developer Handbook 2019 – Learn the entire JavaScript, CSS and HTML development practice!]
- [Google’s Python Class | Python Education | Google Developers]
- [Learn DS & Algorithms | Programiz]
- [List of Keywords in Python Programming]
- [Manning | Catalog]
- [Manning | Deep Learning with Python, Second Edition]
- [Manning | Get Programming]
- [Manning | liveBook]
- [Manning | Making Sense of Edge Computing]
- [Manning | The Quick Python Book, Third Edition]
- [MLOps: Continuous delivery and automation pipelines in machine learning]
- [NumPy Tutorial: Data Analysis with Python — Dataquest]
- [Python – Все для студента]
- [Python | CoderNet]
- [Python 3 для начинающих и чайников – уроки программирования]
- [Python Pandas Tutorial – Tutorialspoint]
- [Python Tricks 101🐍 – HackerNoon.com – Medium]
- [Python Tutorial | Learn Python For Data Science]
- [Python Tutorial for Beginners: Learn Python Programming in 7 Days]
- [Python на Хабре / Хабр]
- [Python/Учебник Python 3.1 — Викиучебник]
- [Scipy Tutorial: Vectors and Arrays (Linear Algebra) – DataCamp]
- [skromnitsky/awesome: 😎 Awesome lists about all kinds of interesting topics]
- [Stencil Computations with Numba — Dask Examples documentation]
- [The Ultimate Guide to Python: How to Go From Beginner to Pro]
- [Tutorials – Online Data Analysis & Interpretation | DataCamp]
- [www.ПЕРВЫЕ ШАГИ.ru :: Шаг 38 – PL/SQL – вводный курс]
- [Вычислительная Фотография :: Будущее фотографии — это код :: Блог Вастрик.ру]
- [Добавляем параллельные вычисления в Pandas / Хабр]
- [Инструменты Python: лучшая шпаргалка для начинающих]
- [Нескучный туториал по NumPy / Хабр]
- [Оглавление — Problem Solving with Algorithms and Data Structures]
- [Основы языка программирования Python за 10 минут / Хабр]
- [Программирование на языке PL/SQL под базы данных Oracle]
- [Руководство Oracle PL/SQL]
- [Содержание E:\DEV\Programming\]
- [Сохраните в закладках эту статью, если вы новичок в Python (особенно если изучаете Python сами) / Хабр]
Books
- [10 лучших книг по программированию по мнению Reddit]
- [15 лучших книг по программированию на Python – Kompot Journal]
- [3 лучших книги по объектно-ориентированному программированию]
- [3 лучших книги по объектно-ориентированному программированию]
- [5 отличных англоязычных книг по теоретическому Computer Science]
- [6 бесплатных книг по алгоритмам в программировании]
- [6.042J Complete course notes]
- [8 книг по компьютерным сетям]
- [Architectural Styles and the Design of Network-based Software Architectures]
- [Build your first app | Android Developers]
- [Building Blocks for Theoretical Computer Science]
- [Computer Networking: a Top Down Approach]
- [Data-Oriented Design]
- [Distributed Systems: Principles and Paradigms]
- [Dive Into Python 3]
- [dmitryrubtsov/Python-for-Data-Science: Education]
- [Domain Driven Design Quickly]
- [Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.]
- [Eloquent JavaScript]
- [holoviz/hvplot: A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews]
- [How to Design Programs]
- [How to not get caught while web scraping? – Data Driven Investor – Medium]
- [HTML5 и CSS3. Веб-разработка по стандартам нового поколения – Хоган Брайан – Google Книги]
- [Introduction – Выразительный Javascript]
- [Introduction to Computing: Explorations in Language, Logic, and Machines]
- [Introduction to Linear Algebra, 5th Edition]
- [Introduction to Programming in Java · Computer Science]
- [JQuery]
- [Learn Python – Free Interactive Python Tutorial]
- [Learn Python in Y Minutes]
- [Learn Python the Hard Way]
- [Python Documentation contents — Python 3.8.2 documentation]
- [R Tutorial for Beginners: Learning R Programming]
- [Springer has released 65 Machine Learning and Data books for free]
- [Teach Yourself Computer Science]
- [The Functional Art: An Introduction to Information Graphics and Visualization: The Functional Art]
- [The HoTT Book | Homotopy Type Theory]
- [The Python Standard Library — Python 3.8.2 documentation]
- [TheoryOfComputation.dvi]
- [Think Python]
- [tr22.pdf]
- [Tutorial – Learn Python in 10 minutes – Stavros’ Stuff]
- [Tutorials — pandas 1.0.3 documentation]
- [unmaintainable code : Java Glossary]
- [You-Dont-Know-JS/README.md at 2nd-ed · getify/You-Dont-Know-JS]
- [You-Dont-Know-JS/README.md at 2nd-ed · getify/You-Dont-Know-JS]
- [Большая книга веб-дизайна – Терри Фельке-Моррис – Google книги]
- [Каталог книг | VK]
- [Категория:Программирование — Википедия]
- [Книга «Python для сложных задач: наука о данных и машинное обучение» / Блог компании Издательский дом «Питер» / Хабр]
- [Лучший самоучитель по Java для начинающих и продвинутых]
- [Математические основы анализа данных: подборка материалов по вузовской математике]
- [Обложка — A Byte Of Python — русский перевод]
- [Оглавление — Problem Solving with Algorithms and Data Structures]
- [Перевод документации Python 3.x]
- [Помнить все: делимся лучшей шпаргалкой по Python]
- [Топ 10 самых популярных книг по программированию]
- [Учебник по NumPy – Визуализация примеров для быстрого изучения]
Games for Education
- [10 мобильных приложений, которые научат вас программировать]
- [12 бесплатных ресурсов для обучения программированию в игровой форме]
- [House Prices: Advanced Regression Techniques | Kaggle]
- [Learn Git Branching]
- [Play CodeCombat Levels – Learn Python, JavaScript, and HTML | CodeCombat]
- [The Python Challenge]
- [Titanic: Machine Learning from Disaster | Kaggle]
Online education (others)
- [arXiv.org e-Print archive]
- [Code Basics: основы программирования на Javascript]
- [CoderNet Портал для помощи программистам | CoderNet]
- [cs184/284a]
- [CS61C Spring 2015: Great Ideas in Computer Architecture (Machine Structures)]
- [Free JavaScript Course: Code School JavaScript Road Trip Part 1 | Pluralsight]
- [kanaka/mal: mal – Make a Lisp]
- [Learn Basic JavaScript: Declare JavaScript Variables | freeCodeCamp.org]
- [Machine Learning is Fun! – Adam Geitgey – Medium]
- [Machine Learning Mastery]
- [new fast.ai course: A Code-First Introduction to Natural Language Processing · fast.ai]
- [OOP Concept Tutorial in Java – Object Oriented Programming | Java67]
- [Operating Systems: Three Easy Pieces]
- [Programming — Towards Data Science]
- [PyVideo.org]
- [Skiena’s Audio Lectures]
- [Solve Easy Unpack – Py.CheckiO]
- [Web | Google Developers]
- [Why every Data Scientist should use Dask? – Towards Data Science]
- [Открытый курс машинного обучения. Тема 1. Первичный анализ данных с Pandas / Хабр]
- [Упражнения по SQL]
IT-events
Training
- [Day 0: Hello, World. | HackerRank]
- [Problems – LeetCode]
- [Skill Assessment]
- [Solve Python | HackerRank]
- [Solve Python | HackerRank]
Project examples for Junior
- [(1) Python]
- [10 Data Science Projects — Dataquest]
- [10 Great Programming Projects to Improve Your Resume and Learn to Program]
- [13 Project Ideas for Intermediate Python Developers — Real Python]
- [5 Cool Python Project Ideas For Inspiration | Hacker Noon]
- [6 Python Projects For Beginners | Codementor]
- [Building a Simple Chatbot from Scratch in Python (using NLTK)]
- [CodeProject – For those who code]
- [karan/Projects: A list of practical projects that anyone can solve in any programming language.]
- [latest Python project topics and ideas with source code for final year projects – kashipara]
- [Machine Learning Projects | Data Science Projects with Example]
- [Martyr2’s Mega Project Ideas List! – Share Your Project | Dream.In.Code]
- [Neural Network Embedding Recommendation System | Kaggle]
- [Python Project Ideas for Final Year, Python Project Help]
- [Top Python Projects | Easy, Intermediate And Advanced Python Projects | Edureka]
- [Tutorial 2 – Making it interesting — BeeWare 0.3.0 documentation]
Puzzles
- [About – Project Euler]
- [CodeKata]
- [Coderbyte | Code Screening, Challenges, & Interview Prep]
- [Problem set @ Timus Online Judge]
- [Programming Praxis | A collection of etudes, updated weekly, for the education and enjoyment of the savvy programmer]
- [The Daily WTF: Curious Perversions in Information Technology]
- [Задачи для программистов, ответы на задания различной сложности]
- [Мозговой фитнес. Актуальные задачи для прокачки программистских скиллов]
- [Решаем задачи на одномерные и двумерные массивы]
Developer’s Tools
- [(Tutorial) Web Scraping With Python: Beautiful Soup – DataCamp]
- [| fastai]
- [10 Best CSS Frameworks For Frontend Developers in 2020 – GeeksforGeeks]
- [10 лучших материалов для изучения Django]
- [20 short tutorials all data scientists should read (and practice) – Data Science Central]
- [7 Steps to Mastering Machine Learning With Python]
- [A Beginner’s Introduction to Python Web Frameworks : Python]
- [A successful Git branching model » nvie.com]
- [ageitgey/face_recognition: The world’s simplest facial recognition api for Python and the command line]
- [Algorithms – Algorithmia]
- [All Tools — PyViz 0.0.1 documentation]
- [An Intro to Git and GitHub for Beginners (Tutorial)]
- [Apache против Nginx: практические соображения]
- [ARCore – Google Developers]
- [Are you still using Pandas for big data? – Towards Data Science]
- [ArtVk & Bugtrack: Задачи по базам данных. Решение задач по SQL [1]]
- [Awesome Python | LibHunt]
- [awesome-vscode | 🎨 A curated list of delightful VS Code packages and resources.]
- [Azure Machine Learning SDK for Python – Azure Machine Learning Python | Microsoft Docs]
- [Batch convert images to PDF with Python by using Pillow or img2pdf | Solarian Programmer]
- [benfred/py-spy: Sampling profiler for Python programs]
- [Better Code Hub]
- [Big data sets available for free – Data Science Central]
- [Build and deploy your first machine learning web app]
- [Build and run a Python app in a container]
- [Building A Blog Application With Django | Django Central]
- [Building a Microservice in Python – Sonu Sharma – Medium]
- [Caffe | Installation]
- [CAL board – Agile board – Jira]
- [Catalog of Patterns of Enterprise Application Architecture]
- [Chapter 1. Getting to know Redis – Redis in Action]
- [Choosing the right estimator — scikit-learn 0.22.2 documentation]
- [CLI Setup – NativeScript Docs]
- [Cloud Shell]
- [Codacy Onboarding]
- [Codecov]
- [CodePen: Build, Test, and Discover Front-end Code.]
- [colorama · PyPI]
- [Conda Cheat Sheet – Kapeli]
- [Control Room | Home | Automation Anywhere]
- [Coveralls – Test Coverage History & Statistics]
- [CRAN – Package rattle]
- [create-graphql-server — instantly scaffold a GraphQL server]
- [Dash Bootstrap Components]
- [Dash for Beginners – DataCamp]
- [Dashboard : skromnitsky : PythonAnywhere]
- [Dashboard · WakaTime]
- [Dask + Numba for Efficient In-Memory Model Scoring – Capital One Tech – Medium]
- [Data Science with Python: Intro to Data Visualization with Matplotlib]
- [Data: Querying, Analyzing and Downloading: The GDELT Project]
- [Dataset Search]
- [Datasets for Data Mining and Data Science]
- [Django ORM. Добавим сахарку / Хабр]
- [Django в примерах · GitBook (Legacy)]
- [Django на русском]
- [Django Руководство часть 11: Разворачивание сайта на сервере – Изучение веб-разработки | MDN]
- [Download · Bootstrap]
- [Download All Free Textbooks from Springer using Python]
- [Download jQuery | jQuery]
- [Download RequireJS]
- [ekzhu/datasketch: MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble]
- [emmetio/emmet-atom: Emmet support for Atom]
- [Erotemic/ubelt: A Python utility belt containing simple tools, a stdlib like feel, and extra batteries. Hashing, Caching, Timing, Progress, and more made easy!]
- [Exploring your data with just 1 line of Python – Towards Data Science]
- [eyaltrabelsi/pandas-log: The goal of pandas-log is to provide feedback about basic pandas operations. It provides simple wrapper functions for the most common functions that add additional logs]
- [facebook/create-react-app: Set up a modern web app by running one command.]
- [facebookresearch/detectron2: Detectron2 is FAIR’s next-generation platform for object detection and segmentation.]
- [facebookresearch/DrQA: Reading Wikipedia to Answer Open-Domain Questions]
- [facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.]
- [facebookresearch/fastMRI: A large-scale dataset of both raw MRI measurements and clinical MRI images]
- [facebookresearch/habitat-api: A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.]
- [facebookresearch/LAMA: LAnguage Model Analysis]
- [facebookresearch/nevergrad: A Python toolbox for performing gradient-free optimization]
- [facebookresearch/pytext: A natural language modeling framework based on PyTorch]
- [facebookresearch/pytorch_GAN_zoo: A mix of GAN implementations including progressive growing]
- [facebookresearch/VideoPose3D: Efficient 3D human pose estimation in video using 2D keypoint trajectories]
- [facebookresearch/visdom: A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.]
- [facebookresearch/vizseq: An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)]
- [Getting started — Flexx 1.0 documentation]
- [Getting started — HiPlot 0.1.9.post2 documentation]
- [Getting started — pandas 1.0.3 documentation]
- [Getting started — SciPy.org]
- [Getting started with Django | Django]
- [Getting started with PyMC3 — PyMC3 3.8 documentation]
- [github/hub: A command-line tool that makes git easier to use with GitHub.]
- [Graphene-Python]
- [great-expectations/great_expectations: Always know what to expect from your data.]
- [gto76/python-cheatsheet: Comprehensive Python Cheatsheet]
- [GUI (графический интерфейс пользователя) | Python 3 для начинающих и чайников]
- [GuiProgramming – Python Wiki]
- [Hello, App Center]
- [How to deploy ML models using Flask + Gunicorn + Nginx + Docker]
- [How to Get a Job with Python – Towards Data Science]
- [How to Install and Run Hadoop on Windows for Beginners – Data Science Central]
- [How to Update All Python Packages | ActiveState]
- [Installation — Kivy 1.11.1 documentation]
- [Installation — pyglet v1.5.0]
- [Integrating Summernote WYSIWYG Editor in Django | Django Central]
- [interpretml/interpret: Fit interpretable machine learning models. Explain blackbox machine learning.]
- [Introducing Bamboolib — a GUI for Pandas – Towards Data Science]
- [Introducing GitFlow]
- [ipinfo.io/json]
- [ironmussa/Optimus at develop-3.0]
- [japronto/1_hello.md at master · squeaky-pl/japronto]
- [jaybaird/python-bloomfilter: Scalable Bloom Filter implemented in Python]
- [jazzband/pip-tools: A set of tools to keep your pinned Python dependencies fresh.]
- [Jetware – aise / tensorflow18_keras21_python36_cpu_notebook – 180509 appliance]
- [jiffyclub/snakeviz: An in-browser Python profile viewer]
- [JS Bin – Collaborative JavaScript Debugging]
- [Keras Cheat Sheet: Neural Networks in Python – DataCamp]
- [keyboard-shortcuts-windows.pdf]
- [knockknock/README.md at master · huggingface/knockknock]
- [Laravel Nova – Beautifully-designed administration panel for Laravel]
- [localhost:54321/callback?code=b7e3a07c1695c5b58b6d]
- [Machine Learning]
- [main]
- [marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier]
- [MIT App Inventor 2]
- [More Itertools — more-itertools 8.2.0 documentation]
- [mouradmourafiq/pandas-summary: An extension to pandas dataframes describe function.]
- [Native mobile apps with Angular, Vue.js, TypeScript, JavaScript – NativeScript]
- [nicolaskruchten/pivottable: Open-source Javascript Pivot Table (aka Pivot Grid, Pivot Chart, Cross-Tab) implementation with drag’n’drop.]
- [NLTK Data]
- [NoSQL Databases List by Hosting Data – Updated 2020]
- [Numba: A High Performance Python Compiler]
- [Numpy and Scipy Documentation — Numpy and Scipy documentation]
- [NumPy в Python. Часть 1 / Хабр]
- [Optimus/README.md at master · ironmussa/Optimus]
- [Over 150 of the Best Machine Learning, NLP, and Python Tutorials I’ve Found]
- [Overview — Matplotlib 3.2.1 documentation]
- [Overview — NumPy v1.19.dev0 Manual]
- [PageSpeed Insights]
- [pallets/werkzeug: The comprehensive WSGI web application library.]
- [Pivot Demo From Local CSV]
- [PivotTable.js]
- [Plotting Google Sheets data in Python with Folium – Towards Data Science]
- [Plugin Status · WakaTime]
- [Polymer Project]
- [Popper – Tooltip & Popover Positioning Engine]
- [PostgreSQL : Документация : Компания Postgres Professional]
- [Prisma – Database tools for modern application development]
- [Projects – Home]
- [pydqc/README.md at master · SauceCat/pydqc]
- [PyQt5 book with a foreword by the creator of PyQt]
- [Pythia’s Documentation — Pythia 0.3 documentation]
- [Python 3.8 documentation — DevDocs]
- [Python Extension Packages for Windows – Christoph Gohlke]
- [Python Frameworks Comparison: How to Choose the Best for Web Development]
- [Python в три ручья: работаем с потоками (часть 1) | GeekBrains – образовательный портал]
- [pytorch3d/INSTALL.md at master · facebookresearch/pytorch3d]
- [Qt Designer Download for Windows and Mac]
- [Quick Start | GatsbyJS]
- [Quick Start · gulp.js]
- [Quickstart for Python/WSGI applications — uWSGI 2.0 documentation]
- [Quickstart tutorial — NumPy v1.19.dev0 Manual]
- [R Packages – RStudio]
- [RaRe-Technologies/bounter: Efficient Counter that uses a limited (bounded) amount of memory regardless of data size.]
- [React — JavaScript-бібліотека для створення користувацьких інтерфейсів]
- [Roundup of Python NLP Libraries – NLP-FOR-HACKERS]
- [samuelhwilliams/Eel: A little Python library for making simple Electron-like HTML/JS GUI apps]
- [SciPy — SciPy v1.4.1 Reference Guide]
- [SciPy.org — SciPy.org]
- [Settings | Account · WakaTime]
- [shaypal5/cachier: Persistent, stale-free, local and cross-machine caching for Python functions.]
- [sindresorhus/awesome: 😎 Awesome lists about all kinds of interesting topics]
- [skromnitsky/My_Projects]
- [Speech Recognition – Speech to Text in Python using Google API, Wit.AI, IBM, CMUSphinx]
- [Speed Up your Algorithms Part 2— Numba – Towards Data Science]
- [Speeding up your Algorithms Part 4— Dask – Towards Data Science]
- [Stop Worrying and Create your Deep Learning Server in 30 minutes]
- [streamlit/streamlit: Streamlit — The fastest way to build custom ML tools]
- [Superbird11/ranges: Continuous Range, RangeSet, and RangeDict data structures for Python]
- [The 30 Best Python Libraries and Packages for Beginners]
- [The Basics of Data Visualisation with Python – Towards Data Science]
- [The Big Bad NLP Database: Access Nearly 300 Datasets]
- [The Coolest Data Science And Machine Learning Tool Companies Of The 2020 Big Data 100]
- [The Most Underrated Python Packages – Towards Data Science]
- [The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks]
- [Tkinter. Программирование GUI на Python. Курс]
- [Top Python Libraries Used In Data Science – Towards Data Science]
- [tqdm/tqdm: A Fast, Extensible Progress Bar for Python and CLI]
- [Travis CI]
- [Travis CI – Test and Deploy with Confidence]
- [Turn Python Scripts into Beautiful ML Tools – Towards Data Science]
- [Tutorial — ZODB documentation]
- [Tutorial: Web Scraping in R with rvest — Dataquest]
- [ucg8j/awesome-dash: A curated list of awesome Dash (plotly) resources]
- [umdjs/umd: UMD (Universal Module Definition) patterns for JavaScript modules that work everywhere.]
- [Understanding the GitHub flow · GitHub Guides]
- [Untitled Diagram – diagrams.net]
- [Untitled Document – Creately]
- [Usage · s0md3v/XSStrike Wiki]
- [User’s Guide — Matplotlib 3.2.1 documentation]
- [vaexio/vaex: Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second 🚀]
- [vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources]
- [vstinner/pyperf: Toolkit to run Python benchmarks]
- [vue.js]
- [vue.min.js]
- [W3Schools Online Web Tutorials]
- [WAVE Report of Мої книги | KUPRIENKO]
- [Web technology for developers | MDN]
- [WebAssembly]
- [Website Style Guide Resources]
- [Welcome to pyjanitor’s documentation! — pyjanitor documentation]
- [Welcome to SymPy’s documentation! — SymPy 1.5.1 documentation]
- [What is Azure Machine Learning | Microsoft Docs]
- [Which movie should I watch? – Nishant Sahoo – Medium]
- [Wolfram Client Library for Python — Wolfram Client Library for Python 1.1.0 documentation]
- [Wolfram|Alpha: Computational Intelligence]
- [Yii PHP Framework]
- [Zsailer/pandas_flavor: The easy way to write your own flavor of Pandas]
- [Введение в потоки в Python – Еще один блог веб разработчика]
- [Введение в создание веб-приложений на Python]
- [Вступ · Django Girls Tutorial]
- [Глава 1: Создание первого приложения · Django в примерах]
- [Данные важнее, чем модели. Как выглядят эффективные процессы в Data Science | DOU]
- [Искусственная нейронная сеть с нуля на Python c библиотекой NumPy]
- [Как написать цепляющую вакансию на ДОУ | DOU]
- [Как оформить профиль на GitHub так, чтобы он работал при поиске работы | DOU]
- [Как получить 100/100 в Google Page Speed Test Tool? — SEO компания UAWEB]
- [Как установить Django, Nginx и Gunicorn на виртуальный сервер]
- [Краткое руководство по Dash — Python веб-фреймворк для создания дэшбордов. Installation + Dash Layout / Хабр]
- [Курс «Hacking PostgreSQL» : Компания Postgres Professional]
- [Лучшие датасеты для машинного обучения и анализа данных]
- [Мега-Учебник Flask, Часть 1: «Привет, Мир!» / Хабр]
- [Многопоточность в Python]
- [Многопоточность в Python. Библиотеки threading и multiprocessing.]
- [Многопоточность на примерах – модуль threading]
- [Настраиваем Django + virtualenv + nginx + gunicorn + PostgreSQL + memcached + letsencrypt на Ubuntu 16.04 | Python 3 для начинающих и чайников]
- [Настройка Django с Postgres, Nginx и Gunicorn в Ubuntu 18.04 | DigitalOcean]
- [Настройка веб-сервера для Django с nginx и uWSGI – Как стать программистом]
- [Обработка естественного языка: с чего начать и что изучать дальше]
- [Объектно-ориентированное Программирование в Python]
- [Описания паттернов проектирования. Паттерны проектирования. Шаблоны проектирования на Design pattern ru]
- [Перші кроки в NLP: розглядаємо Python-бібліотеку TensorFlow та нейронні мережі в реальному завданні | DOU]
- [Почему CSS Grid лучше, чем фреймворк Bootstrap?]
- [Почему Python хорош для Data Science и разработки приложений]
- [Предсказываем будущее с помощью библиотеки Facebook Prophet / Блог компании Open Data Science / Хабр]
- [Примеры использования Python-библиотеки NumPy | Записки программиста]
- [Скринкаст по Git]
- [Создаем простой калькулятор в PyQt5]
- [Создание графического интерфейса на Python 3 с Tkinter ~ PythonRu]
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