Awesome-Python-Learning v.1.2.0

Full list of links

See full list with categories in Awesome_Python_Learning.csv - 1520 links!

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]

• [Python Tutorial for Beginners]

• [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\]](file:///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

• [Календар IT-подій в Києві | DOU]

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]

• [25 Exciting Python Project Ideas & Topics for Beginners 2020 | upGrad blog]

• [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]

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