1000 бесплатных онлайн-курсов по программированию, актуальные в 2023 году.

Двенадцать лет назад такие университеты, как Стэнфорд и Массачусетский технологический институт, открыли для публики бесплатные онлайн-курсы. Сегодня более 1200 школ по всему миру создали тысячи бесплатных онлайн-курсов.

Чтобы поприветствовать новый год, я составил этот список из 1000+ таких бесплатных онлайн-курсов, которые вы можете начать прямо сейчас. Для этого я использовал базу данных Class Central, содержащую более 100 000 онлайн-курсов. Если в каталог были оценки курсов, я включил их средний рейтинг. Это самый большой каталог курсов доступных в сети.

Я отсортировал эти курсы по следующим категориям в зависимости от уровня сложности:

Новичок
Средний
Сеньор
Курсы, предлагаемые впервые, отмечены как [Beginner]. Почти все эти курсы предназначены для самостоятельного изучения, то есть вы можете начать прямо сейчас.с.

Наконец, если у вас возникли проблемы с тем, чтобы понять, как бесплатно записаться на курсы Coursera, не волнуйтесь — я заканчиваю статью и скоро выложу ее на нашем сайте https://uproger.com/

@sqlhub – sql анализ данных в телеграме. Первоисточник всех материалов по работе с базами данных.

Этот список будет постоянно пополняться.

Поехали!

Новчкам

• Elements of AI from University of Helsinki ★★★★★(713)
• Трудоустройство для разработчиков
• Unlocking Information Security I: From Cryptography to Buffer Overflows from Tel Aviv University ★★★★★(298)
• Основы работы в Tableau
• Уроки по Java с нулям
• Alex Marshal: «Как стать Java Developer с нуля и зарабатывать деньги на IT»
• CS50’s Introduction to Computer Science from Harvard University ★★★★★(140)
• «Data Science: будущее для каждого» — «Нетология».
• «Введение в науку о данных» — СПбГУ.
• «Введение в Data Science‎ и машинное обучение» — Институт биоинформатики.
• «Нейронные сети» — Институт биоинформатики.
• «Машинное обучение» — ОмГТУ.
• Computational Social Science Methods from University of California, Davis ★★★★★(107)
• Introduction to HTML5 from University of Michigan ★★★★☆(50)
• «Сертификация в PromoPult. Поисковое продвижение» от CyberMarketing (12 уроков, с сертификатом)
• «Базовый курс по SEO» от Major Academy (14 уроков, без сертификата)
• «Бесплатный курс по линкбилдингу» от Collaborator (16 уроков, без сертификата)
• «Бесплатный курс по семантическому проектированию сайта» от Collaborator (46 уроков, без сертификата)
• «Основы поисковой оптимизации» от ppc.world (7 уроков, без сертификата)
• «Лёгкая семантика 1.0» от Кирилла Рамираса (5 уроков, без сертификата)
• «SEO» от «Школы SEO» (19 уроков, без сертификата)
• YouTube-плейлист «SEO Продвижение» от SEOquick (96 видео, без сертификата)
• «Бесплатные Уроки SEO Продвижения» от «Академии SEO» (82 видео, без сертификата)
• «Бесплатный видеокурс по SEO-продвижению» от Александра Алаева (7 видео, без сертификата)
• Unlocking Information Security II: An Internet Perspective from Tel Aviv University ★★★★★(50)
• Internet History, Technology, and Security from University of Michigan ★★★★★(41)
• Introduction to Linux from Linux Foundation ★★★★☆(37)
• Introduction to Databases from Stanford University ★★★★★(30)
• Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course) from Hebrew University of Jerusalem ★★★★★(28)
• Fundamentos TIC para profesionales de negocios: Desarrollo de Software from Universitat Politècnica de València ★★★★☆(26)
• [New] Introduction to Quantum Computing from The University of British Columbia
• [New] Coding Interview Preparation from Meta
• [New] Software Development Practices from Meta
• Introduction to Cyber Security from The Open University ★★★★☆(22)
• Web Security Fundamentals from KU Leuven University ★★★★☆(22)
• CS50’s Web Programming with Python and JavaScript from Harvard University ★★★★★(21)
• HTML, CSS, and Javascript for Web Developers from Johns Hopkins University ★★★★★(20)
• Computer Science 101 from Stanford University ★★★★☆(18)
• Programming Basics from Indian Institute of Technology Bombay ★★★☆☆(18)
• Diagramas UML estructurales para la Ingeniería del Software from Universitat Politècnica de València ★★★★★(17)
• Fundamentos TIC para profesionales de negocios: Aplicaciones empresariales from Universitat Politècnica de València ★★★★★(16)
• Introduction to Networking from New York University (NYU) ★★★★☆(16)
• Introduction to CSS3 from University of Michigan ★★★★★(14)
• CS50’s Computer Science for Business Professionals from Harvard University ★★★★★(13)
• Getting Started with AWS Machine Learning from Amazon Web Services ★★★★☆(13)
• Building AI from University of Helsinki ★★★★☆(13)
• Introduction to the Internet of Things and Embedded Systems from University of California, Irvine ★★★★☆(12)
• «Машинное обучение в финансах» — «СберУниверситет».
• «Анализ данных в R‎» — Институт биоинформатики.
• «Анализ данных в Google Analytics» — Андрей Осипов.
• «Теория вероятностей для начинающих» — МФТИ.
• «‎Анализ данных просто и доступно» — Игорь Клейнер.
• «Математические методы в психологии. Основы применения‎» — СПбГУ.
• «Базовые навыки Excel‎» — SF Education.
• «Квантовые вычисления» — СПбГУ.
• «Анализ данных» — РЭУ им. Г.В. Плеханова.
• «Практики оперативной аналитики в MS Excel‎» — СПбГУ.
• «Исследование статистических взаимосвязей» — НГУ совместно с «2ГИС».
• «Основы статистики» — Институт биоинформатики.
• «Знакомство с R ‎и базовая статистика» — СПбГУ.
• «Статистика для гуманитариев» — ТГУ.
• «Эконометрика» — НИУ ВШЭ.
• «Быстрый старт в искусственный интеллект» — МФТИ.
• «‎Введение в информационный поиск» — МФТИ совместно с Mail.ru Group.
• «Основы Python и анализа данных» — «Яндекс.Практикум».
• «Математическая статистика‎» — Computer Science Center.
• «BI-разработчик. Основы работы в Tableau» — Артём Прытков.
• «Hadoop. Система для обработки больших объёмов данных» — Mail.ru Group.
• «Теория игр» — МФТИ.
• «A Crash Course in Data Science» — Университет Джонса Хопкинса.
• «Introduction to Data Science» — Alison.
• «Learn Data Science» — Dataquest.
• «Data Science» — Гарвардский университет.
• «Introduction to Data Science in Python» — Мичиганский университет.
• «Learn Data Science With R Part 1 of 10» — Ram Reddy.
• «Introduction to Data Science using Python» — Rakesh Gopalakrishnan.
• «Learning to Love Statistics» — Нотрдамский университет.
• Data Science: Wrangling. На курсе научитесь обрабатывать и преобразовывать необработанные данные в форматы, необходимые для анализа.
• Data Science: Visualization. Изучите основные принципы визуализации данных.
• Data Science: Machine Learning. На курсе изучите машинное обучение. Создатите систему рекомендаций фильмов и изучите научные основы одного из самых популярных и успешных методов обработки данных.
• Principles, Statistical and Computational Tools for Reproducible Data Science. Изучите ряд концепций, моделей мышления, парадигм анализа, а также вычислительных и статистических инструментов, которые используются в науке о данных.
• Data Science: Linear Regression. Узнайте, как использовать R для реализации линейной регрессии, одного из наиболее распространенных подходов к статистическому моделированию в науке о данных.
• Введение в веб-аналитику от Якова Осипенкова.
• Профессия маркетолог-аналитик от MAED.
• Веб-аналитика для принятия решений.
• Web-аналитик 2.0 от ConvertMonster.
• 1. Платформа Стэнфордского университета, на которой также можно найти неплохие курсы для разного уровня.
• 2. Курс «Теория вероятностей для начинающих».
• Лучше Андрея Райгородского — преподавателя курса — никто не объяснит эту тему. Разжёвывает всё, даёт понятные примеры. Курс однозначно стоит внимания.
• 3. Курс «Основы статистики. Часть 2».
• После основ статистики можно продолжить углублять знания в данной теме и пройти второй курс. Анатолий Карпов излагает материал максимально понятно и просто.
• 4. Курс «Нейронные сети».
• Очередной отличный курс от Института биоинформатики. Для начинающих, возможно, будет немного сложно. Но курс в любом случае стоит внимания.
• 5. «Питонтьютор».
• Сайт поможет изучить основы программирования на Python. Работа проходит прямо в браузере. Сначала читаешь статью, затем решаешь много практических задач от легкого уровня к сложному.
• 6. Курс «Ликбез по дискретной математике».
• t.me/bigdatai -курсы и бесплатные инструментов по машинному обучению.
• CS50’s Introduction to Artificial Intelligence with Python from Harvard University ★★★★★(11)
• Creative Programming for Digital Media & Mobile Apps from University of London International Programmes ★★★★☆(11)
• HTML5 Coding Essentials and Best Practices from World Wide Web Consortium (W3C) ★★★★☆(11)
• CS50’s Understanding Technology from Harvard University ★★★★★(10)
• Technical Support Fundamentals from Google ★★★★☆(10)
• Learn to Program: Crafting Quality Code from University of Toronto ★★★★☆(9)
• Usable Security from University of Maryland, College Park ★★★☆☆(9)
• Computer Hardware and Operating Systems from New York University (NYU) ★★★★★(9)
• Linux Command Line Basics
• Intro to Relational Databases
• How To Create a Website in a Weekend! (Project-Centered Course) from State University of New York ★★★★☆(7)
• Introducción a la programación en C: Instrucciones de control y ficheros de texto from Universidad Autónoma de Madrid ★★★★★(7)
• AI For Everyone from DeepLearning.AI ★★★★★(6)
• CS50’s Computer Science for Lawyers from Harvard University ★★★★★(5)
• Introduction to Computing using Python from Georgia Institute of Technology ★★★★★(5)
• Introduction to the Internet of Things from Universitat Politècnica de València ★★★★☆(5)
• Paradigms of Computer Programming – Fundamentals from Université catholique de Louvain ★★★★★(5)
• Paradigms of Computer Programming – Abstraction and Concurrency from Université catholique de Louvain ★★★★☆(5)
• Web Coding Fundamentals: HTML, CSS and Javascript from National University of Singapore ★★★★★(5)
• The Computing Technology Inside Your Smartphone from Cornell University ★★★★★(5)
• Basics of Computing and Programming from New York University (NYU) ★★★★☆(5)
• C for Everyone: Programming Fundamentals from University of California, Santa Cruz ★★★★☆(5)
• Programming in Scratch from Harvey Mudd College ★★★★★(5)
• Web Applications for Everybody
• Problem Solving, Python Programming, and Video Games from University of Alberta ★★★★☆(4)
• Full Stack open 2022 from University of Helsinki ★★★★★(4)
• CS For All: Introduction to Computer Science and Python Programming from Harvey Mudd College ★★★★★(4)
• CS50’s Introduction to Game Development from Harvard University ★★★★☆(3)
• How Computers Work from University of London International Programmes ★★★★☆(3)
• Introduction to Web Development from University of California, Davis ★★★★☆(3)
• Python Programming Essentials from Rice University ★★★★★(3)
• Web Development and Design using WordPress from California Institute of the Arts ★★★★☆(3)
• Object-Oriented Programming from Indian Institute of Technology Bombay ★★★☆☆(3)
• C Programming: Modular Programming and Memory Management from Dartmouth College ★★★☆☆(3)
• Introduction to Structured Query Language (SQL) from University of Michigan ★★★★☆(2)
• The Beauty and Joy of Computing – AP® CS Principles Part 1 from University of California, Berkeley ★★★★★(2)
• Introduction to Accounting Data Analytics and Visualization from University of Illinois at Urbana-Champaign ★★★★★(2)
• Software Engineering: Introduction from The University of British Columbia ★★★☆☆(2)
• Web Design: Strategy and Information Architecture from California Institute of the Arts ★★★★★(2)
• Introduction to Software Testing from University of Minnesota ★★★★★(2)
• TCP/IP and Advanced Topics from University of Colorado System ★★★★☆(2)
• Introduction to Cybersecurity for Business from University of Colorado System ★★★★★(2)
• Introduzione all’informatica from University of Naples Federico II ★★★★★(2)
• Introduction to the Internet of Things (IoT) from Curtin University ★★★☆☆(2)
• C Programming: Pointers and Memory Management from Dartmouth College ★★★★★(2)
• C Programming: Language Foundations from Dartmouth College ★★★★★(2)
• Linux Basics: The Command Line Interface from Dartmouth College ★★★★★(2)
• C Programming: Using Linux Tools and Libraries from Dartmouth College ★★★★★(2)
• Think. Create. Code from University of Adelaide ★★★★★(2)
• Introduction to HTML and JavaScript from Microsoft ★★★★★(2)
• Introduction to NodeJS from Microsoft ★★★★★(2)
• Introduction to Database Queries from New York University (NYU) ★★★★★(2)
• Software Engineering Essentials from Technische Universität München (Technical University of Munich) ★★★★☆(2)
• Introducción a la programación en Python I: Aprendiendo a programar con Python from Pontificia Universidad Católica de Chile ★★★★★(2)
• MongoDB Basics
• CS50’s AP® Computer Science Principles from Harvard University ★★★★★(1)
• CS50’s Mobile App Development with React Native from Harvard University ★★★★☆(1)
• Databases: JSON Data from Stanford University ★☆☆☆☆(1)
• Building Database Applications in PHP from University of Michigan ★★★★★(1)
• Building Web Applications in Django from University of Michigan ★★★★★(1)
• Computer Science: Programming with a Purpose from Princeton University ★★★★★(1)
• Introduction to Computer Programming from University of London International Programmes ★★★★★(1)
• Cyber Security Fundamentals from University of London International Programmes ★★★★★(1)
• Principles of Secure Coding from University of California, Davis ★★★★★(1)
• Python Data Visualization from Rice University ★★★★★(1)
• Programming with Scratch from The Hong Kong University of Science and Technology ★★☆☆☆(1)
• Cyber Security Economics from Delft University of Technology ★★☆☆☆(1)
• Proactive Computer Security from University of Colorado System ★★★★★(1)
• Introduction à la programmation orientée objet (en Java) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
• NoSQL Databases from University of Maryland, Baltimore County ★★☆☆☆(1)
• Introduction to TCP/IP from Yonsei University ★★★★★(1)
• Introdução à Ciência da Computação com Python Parte 1 from Universidade de São Paulo ★★★★★(1)
• Writing Professional Code from Microsoft ★☆☆☆☆(1)
• AI for Everyone: Master the Basics from IBM ★★★★★(1)
• Introduction to Cloud Computing from IBM ★★★★★(1)
• Introduction to Cyber Attacks from New York University (NYU) ★★★★★(1)
• Lernen objekt-orientierter Programmierung from Technische Universität München (Technical University of Munich) ★★★★★(1)
• Computing Form and Shape: Python Programming with the Rhinoscript Library from Rhode Island School of Design ★★★★★(1)
• MyCS: Computer Science for Beginners from Harvey Mudd College ★★★☆☆(1)
• Diseño Web con HTML5 + CSS from Universitas Telefónica ★☆☆☆☆(1)
• Data Privacy Fundamentals from Northeastern University ★★★★★(1)
• ES6 – JavaScript Improved
• Applications of TinyML from Harvard University
• Deploying TinyML from Harvard University
• Databases: Unified Modeling Language from Stanford University
• Databases: Indexes and Transactions from Stanford University
• Databases: On-Line Analytical Processing from Stanford University
• Databases: OLAP and Recursion from Stanford University
• Databases: Semistructured Data from Stanford University
• Databases: Modeling and Theory from Stanford University
• Hacker Tools from Massachusetts Institute of Technology
• Understanding the World Through Data from Massachusetts Institute of Technology
• Computational Thinking for Problem Solving from University of Pennsylvania
• AI Fundamentals for Non-Data Scientists from University of Pennsylvania
• Django Features and Libraries from University of Michigan
• Web Application Technologies and Django from University of Michigan
• Web Application Technologies and Django from University of Michigan
• Database Architecture, Scale, and NoSQL with Elasticsearch from University of Michigan
• The Power of Object-Oriented Programming from University of Michigan
• Introduction to DevSecOps from Johns Hopkins University
• The Blockchain System from University of California, Irvine
• Data, Security, and Privacy from University of California, Irvine
• Productivity and Systems Development from University of California, Irvine
• The Nature of Data and Relational Database Design from University of California, Irvine
• The Beauty and Joy of Computing (CS Principles), Part 1 from University of California, Berkeley
• The Beauty and Joy of Computing – AP® CS Principles Part 2 from University of California, Berkeley
• The Beauty and Joy of Computing (CS Principles), Part 4 from University of California, Berkeley
• The Beauty and Joy of Computing (CS Principles), Part 3 from University of California, Berkeley
• Programming Fundamentals from Duke University
• Interacting with the System and Managing Memory from Duke University
• Introduction to Programming and Animation with Alice from Duke University
• Cloud Computing Foundations from Duke University
• Human Factors in AI from Duke University
• Big Data Analytics in Healthcare from Georgia Institute of Technology
• Data Analysis and Visualization from Georgia Institute of Technology
• Introduction to Cybersecurity from University of Washington
• Introduction to Internationalization and Localization from University of Washington
• Applied Analytics and Data for Decision Making from University at Buffalo
• Building Interactive 3D Characters and Social VR from University of London International Programmes
• Coding for Designers, Managers, & Entrepreneurs I from University of Virginia
• Coding for Designers, Managers, & Entrepreneurs II from University of Virginia
• Coding for Designers, Managers, & Entrepreneurs III from University of Virginia
• Artificial Intelligence in Marketing from University of Virginia
• Identifying Security Vulnerabilities from University of California, Davis
• Evidence and Data Collection for Problem Solving from University of Leeds
• Python Data Analysis from Rice University
• Введение в базы данных from St. Petersburg State Polytechnic University
• Cloud Security Basics from University of Minnesota
• «Вводный курс по контекстной рекламе» от «Яндекс.Практикум» (10 часов на освоение материала, без сертификата)
• «Основы контекстной рекламы: Яндекс.Директ» от «Нетологии» (9 уроков, с сертификатом)
• «Яндекс.Директ: подготовка к сертификации» от «Нетологии» (8 часов на освоение материала, с сертификатом)
• «Яндекс.Директ простыми словами» от «Яндекса» (5 уроков, без сертификата)
• «Как разместить рекламу в Директе» от «Яндекса» (10 уроков, без сертификата)
• «Показатели эффективности рекламы» от «Яндекса» (4 урока, без сертификата)
• «Кому доверить запуск рекламы в интернете» от «Яндекса» (7 уроков, без сертификата)
• «Контекстная реклама: от основ до повышения эффективности» от eLama (12 уроков, без сертификата)
• «Специалист по Яндекс.Директу» от ppc.world (41 урок, без сертификата)
• «Основы Google Ads» от ppc.world (35 уроков, без сертификата)
• «Контекстная реклама» от CyberMarketing (6 уроков, с сертификатом)
• Foundations of Data Analytics from The Hong Kong University of Science and Technology
• AP Computer Science A: Java Programming Classes and Objects from Purdue University
• AP Computer Science A: Java Programming Loops and Data Structures from Purdue University
• AP Computer Science A: Java Programming Polymorphism and Advanced Data Structures from Purdue University
• Cybersecurity for Everyone from University of Maryland, College Park
• What is “the mind” and what is artificial intelligence? from University of Colorado Boulder
• Cybersecurity for Data Science from University of Colorado Boulder
• Trees and Graphs: Basics from University of Colorado Boulder
• Data Science as a Field from University of Colorado Boulder
• Fundamentals of Data Visualization from University of Colorado Boulder
• Relational Database Design from University of Colorado Boulder
• Scratch: Programmeren voor kinderen (8+) from Delft University of Technology
• AI in Practice: Preparing for AI from Delft University of Technology
• AI in Practice: Applying AI from Delft University of Technology
• Software Design Methods and Tools from University of Colorado System
• Software Design as an Element of the Software Development Lifecycle from University of Colorado System
• Software Design as an Abstraction from University of Colorado System
• Shell Programming – A necessity for all Programmers from Indian Institute of Technology Bombay
• Basi di dati from University of Naples Federico II
• Programmazione I from University of Naples Federico II
• Foundations of Data Science from Indian Institute of Management Bangalore
• Relational Database Design from University System of Maryland
• Relational Database Management Systems from University System of Maryland
• Video Game Design and Balance from Rochester Institute of Technology
• Deep Learning for Business from Yonsei University
• Technologies and platforms for Artificial Intelligence from Politecnico di Milano
• Cyber Security Basics: A Hands-on Approach from Universidad Carlos iii de Madrid
• Introducción a UML from Universidad de los Andes
• Web of Data from EIT Digital
• Blockchain for the decision maker from EIT Digital
• C Programming: Getting Started from Dartmouth College
• C Programming: Advanced Data Types from Dartmouth College
• Diseñando páginas web con Bootstrap 4 from Universidad Austral
• Introdução à Ciência da Computação com Python Parte 2 from Universidade de São Paulo
• Introduction to Design Thinking from Microsoft
• AI Fundamentals from Microsoft
• Introduction to Web Development with HTML5, CSS3, and JavaScript from IBM
• NoSQL Database Basics from IBM
• Relational Database Administration (DBA) from IBM
• Introduction to Web Development with HTML, CSS, JavaScript from IBM
• Introduction to DevOps from IBM
• Cyber Attack Countermeasures from New York University (NYU)
• Information Security – Authentication and Access Control from New York University (NYU)
• Penetration Testing – Exploitation from New York University (NYU)
• A Beginner’s Guide to Becoming a Blockchain Developer with Overledger from King’s College London
• Introduction to Quantum Computing for Everyone from The University of Chicago
• Introduction to Quantum Computing for Everyone 2 from The University of Chicago
• Machine Learning: Concepts and Applications from The University of Chicago
• Introduction to Blockchain Technology and Applications from University College London
• Introduction to Open Source Networking Technologies from Linux Foundation
• Data and AI Fundamentals from Linux Foundation
• Programming Languages Ⅰ from Korea Advanced Institute of Science and Technology
• Programming Languages Ⅱ from Korea Advanced Institute of Science and Technology
• C for Everyone: Structured Programming from University of California, Santa Cruz
• Data Visualization for All from Trinity College
• Mobile Computing with App Inventor – CS Principles from The University of Warwick
• プログラミングしながら学ぶコンピュータサイエンス入門 : Introduction to Computer Science and Programming from Tokyo Institute of Technology
• Introduction to Computer Science and Programming from Tokyo Institute of Technology
• Understanding Quantum Computers from Keio University
• DevOps with Kubernetes from University of Helsinki
• DevOps with Docker from University of Helsinki
• Programming with GUIs from Raspberry Pi Foundation
• Programming 102: Think Like a Computer Scientist from Raspberry Pi Foundation
• Machine Learning Basics from Sungkyunkwan University
• Introduction to MongoDB from MongoDB University
• Programación Orientada a Objetos (POO) from MéxicoX
• Information Technology Foundations from Western Governors University
• Scripting and Programming Foundations from Western Governors University
• HTTP & Web Servers

Средний уровень

• Using Databases with Python from University of Michigan ★★★★★(4060)
• R Programming from Johns Hopkins University ★★★☆☆(246)
• The Data Scientist’s Toolbox from Johns Hopkins University ★★★☆☆(166)
• Machine Learning for Musicians and Artists from Goldsmiths University of London ★★★★★(89)
• Divide and Conquer, Sorting and Searching, and Randomized Algorithms from Stanford University ★★★★★(68)
• Functional Programming Principles in Scala from École Polytechnique Fédérale de Lausanne ★★★★★(66)
• Data Science and Agile Systems for Product Management from University System of Maryland ★★★★★(62)
• Algorithms, Part I from Princeton University ★★★★★(59)
• Getting and Cleaning Data from Johns Hopkins University ★★★☆☆(57)
• Cryptography I from Stanford University ★★★★★(53)
• Intelligenza Artificiale from University of Urbino ★★★★★(49)
• Python for Data Science from University of California, San Diego ★★★★☆(47)
• Introduction to Data Science in Python from University of Michigan ★★☆☆☆(46)
• Object-Oriented Design from University of Alberta ★★★★☆(39)
• Introduction to Big Data from University of California, San Diego ★★★☆☆(35)
• Making Sense of Data in the Media from The University of Sheffield ★★★★★(35)
• Statistical Inference from Johns Hopkins University ★★★☆☆(34)
• Regression Models from Johns Hopkins University ★★★☆☆(34)
• Probability and Statistics in Data Science using Python from University of California, San Diego ★★☆☆☆(31)
• CS188.1x: Artificial Intelligence from University of California, Berkeley ★★★★★(30)
• Principles of Computing (Part 1) from Rice University ★★★★★(30)
• Reproducible Research from Johns Hopkins University ★★★★☆(27)
• Practical Machine Learning from Johns Hopkins University ★★★☆☆(27)
• Programming Languages, Part A from University of Washington ★★★★★(27)
• Responsive Website Basics: Code with HTML, CSS, and JavaScript from University of London International Programmes ★★★★☆(27)
• Mining Massive Datasets from Stanford University ★★★★★(25)
• A Crash Course in Data Science from Johns Hopkins University ★★★★☆(25)
• Design Patterns from University of Alberta ★★★★★(25)
• Software Security from University of Maryland, College Park ★★★★☆(24)
• Algorithmic Toolbox from University of California, San Diego ★★★★☆(23)
• Introducción a la Inteligencia Artificial: Principales Algoritmos from Galileo University ★★★★★(22)
• Algorithms, Part II from Princeton University ★★★★★(21)
• Cloud Computing Concepts, Part 1 from University of Illinois at Urbana-Champaign ★★★☆☆(21)
• Data Visualization from University of Illinois at Urbana-Champaign ★★★☆☆(21)
• Learning From Data (Introductory Machine Learning) from California Institute of Technology ★★★★★(21)
• Statistics and R from Harvard University ★★★★☆(20)
• Automata Theory from Stanford University ★★★★☆(20)
• Introduction to Machine Learning Course from Stanford University ★★★★☆(20)
• Data Analysis with R from Facebook ★★★★★(18)
• MongoDB for Java Developers
• Process Mining: Data science in Action from Eindhoven University of Technology ★★★★☆(17)
• Data Structures from University of California, San Diego ★★★★☆(16)
• Principles of Computing (Part 2) from Rice University ★★★★☆(16)
• Software Architecture from University of Alberta ★★★★☆(16)
• How to Code: Simple Data from The University of British Columbia ★★★★☆(15)
• Algorithmic Thinking (Part 1) from Rice University ★★★★☆(15)
• The Nature of Code from Processing Foundation ★★★★★(15)
• Design of Computer Programs from Stanford University ★★★★☆(14)
• Python for Genomic Data Science from Johns Hopkins University ★★★☆☆(14)
• Building a Data Science Team from Johns Hopkins University ★★★★☆(14)
• Text Retrieval and Search Engines from University of Illinois at Urbana-Champaign ★★★☆☆(14)
• Responsive Web Design from University of London International Programmes ★★★★☆(14)
• Data Analysis: Take It to the MAX() from Delft University of Technology ★★★☆☆(13)
• Intro to Data Science
• Using Python for Research from Harvard University ★★★★☆(12)
• Data Science in Real Life from Johns Hopkins University ★★★☆☆(12)
• Data Science Math Skills from Duke University ★★★★☆(12)
• Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues from Georgia Institute of Technology ★★★★★(12)
• Discrete Optimization from University of Melbourne ★★★★☆(12)
• Introduction to Software Product Management from University of Alberta ★★★★☆(12)
• Data Science: R Basics from Harvard University ★★★★★(11)
• Interactivity with JavaScript from University of Michigan ★★★★☆(11)
• Human-Computer Interaction I: Fundamentals & Design Principles from Georgia Institute of Technology ★★★★★(11)
• Biology Meets Programming: Bioinformatics for Beginners from University of California, San Diego ★★★☆☆(10)
• Programming Languages from University of Virginia ★★★☆☆(10)
• Learning from Data (Introductory Machine Learning course) from California Institute of Technology ★★★★★(10)
• Full Stack Foundations
• Managing Data Analysis from Johns Hopkins University ★★★☆☆(9)
• Data Visualization and Communication with Tableau from Duke University ★★★★☆(9)
• Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure from University of Illinois at Urbana-Champaign ★★★☆☆(9)
• Algorithmic Thinking (Part 2) from Rice University ★★★★☆(9)
• Data Wrangling with MongoDB from MongoDB University ★★★☆☆(9)
• Advanced Styling with Responsive Design from University of Michigan ★★★★☆(8)
• Machine Learning Fundamentals from University of California, San Diego ★★★★☆(8)
• Foundations of Data Analysis – Part 1: Statistics Using R from The University of Texas at Austin ★★★★☆(8)
• Cryptography from University of Maryland, College Park ★★★★☆(8)
• MATLAB and Octave for Beginners from École Polytechnique Fédérale de Lausanne ★★★★☆(8)
• Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital from Duke University ★★★★☆(7)
• Guided Tour of Machine Learning in Finance from New York University (NYU) ★☆☆☆☆(7)
• Software Testing from University of Utah ★★★★☆(7)
• Intro to DevOps from Nutanix ★★★☆☆(7)
• Computer Graphics from University of California, San Diego ★★★★☆(6)
• Data Structures and Performance from University of California, San Diego ★★★★☆(6)
• Internet of Things: How did we get here? from University of California, San Diego ★★☆☆☆(6)
• Computer Architecture from Princeton University ★★★★☆(6)
• Analysis of Algorithms from Princeton University ★★★★☆(6)
• Managing Big Data with MySQL from Duke University ★★★★☆(6)
• Computer Networking from Georgia Institute of Technology ★★★★☆(6)
• Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps from Georgia Institute of Technology ★★★★★(6)
• Cloud Computing Concepts: Part 2 from University of Illinois at Urbana-Champaign ★★★★★(6)
• Web Application Development with JavaScript and MongoDB from University of London International Programmes ★★★★☆(6)
• Introduction to Meteor.js Development from University of London International Programmes ★★★★☆(6)
• Client Needs and Software Requirements from University of Alberta ★★★★★(6)
• Interactive Computer Graphics from University of Tokyo ★★★☆☆(6)
• Fundamentals of Machine Learning from Santa Fe Institute ★★★★★(6)
• Software Debugging from Saarland University ★★★★★(6)
• Intro to Algorithms
• Intro to AJAX
• Intro to Data Analysis
• Networking for Web Developers
• Software Construction in Java from Massachusetts Institute of Technology ★★★★★(5)
• Internet of Things: Setting Up Your DragonBoard™ Development Platform from University of California, San Diego ★★★☆☆(5)
• Data Structures: An Active Learning Approach from University of California, San Diego ★★★★★(5)
• Software Development Process from Georgia Institute of Technology ★★★★☆(5)
• Cloud Networking from University of Illinois at Urbana-Champaign ★★★★☆(5)
• Social Network Analysis from University of California, Davis ★★★★★(5)
• Database Management Essentials from University of Colorado System ★★★★☆(5)
• Data Management and Visualization from Wesleyan University ★★☆☆☆(5)
• JavaScript Promises from Google ★★★★★(5)
• Data Science Essentials from Microsoft ★★★★☆(5)
• Programming for Everyone – An Introduction to Visual Programming Languages from Weizmann Institute of Science ★★★★☆(5)
• Parallel Programming Concepts
• Data Visualization and D3.js
• Algorithms on Strings from University of California, San Diego ★★★☆☆(4)
• The R Programming Environment from Johns Hopkins University ★★★☆☆(4)
• Data Manipulation at Scale: Systems and Algorithms from University of Washington ★★★☆☆(4)
• Programming Languages, Part B from University of Washington ★★★★☆(4)
• Data Analysis Tools from Wesleyan University ★★★☆☆(4)
• Querying Data with Transact-SQL from Microsoft ★★★★☆(4)
• Programming with Python for Data Science from Microsoft ★★★★☆(4)
• Practical Numerical Methods with Python from George Washington University ★★★★☆(4)
• Algorithms on Graphs from University of California, San Diego ★★★★☆(3)
• Internet of Things: Communication Technologies from University of California, San Diego ★★★☆☆(3)
• Mastering the Software Engineering Interview from University of California, San Diego ★★★★☆(3)
• Big Data Modeling and Management Systems from University of California, San Diego ★★★☆☆(3)
• Big Data Integration and Processing from University of California, San Diego ★★★★☆(3)
• Algorithmic Design and Techniques from University of California, San Diego ★★★★☆(3)
• Machine Learning: Unsupervised Learning from Brown University ★★★☆☆(3)
• Software Architecture & Design from Georgia Institute of Technology ★★★★★(3)
• Human-Computer Interaction II: Cognition, Context & Culture from Georgia Institute of Technology ★★★★★(3)
• Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms from Georgia Institute of Technology ★★★★★(3)
• Framework for Data Collection and Analysis from University of Maryland, College Park ★★★★☆(3)
• Data Warehouse Concepts, Design, and Data Integration from University of Colorado System ★★★☆☆(3)
• Service-Oriented Architecture from University of Alberta ★★★★☆(3)
• Website Performance Optimization from Google ★★★★☆(3)
• DevOps for Developers: How to Get Started from Microsoft ★★★★☆(3)
• Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course) from Hebrew University of Jerusalem ★★★★★(3)
• Data Mining with Weka from University of Waikato ★★★★☆(3)
• MongoDB for .NET Developers
• Configuring Linux Web Servers
• Language, Proof and Logic from Stanford University ★★★★★(2)
• Mobile Application Experiences Part 1: From a Domain to an App Idea from Massachusetts Institute of Technology ★★★★★(2)
• Software Development Fundamentals from University of Pennsylvania ★★★☆☆(2)
• Building R Packages from Johns Hopkins University ★★★☆☆(2)
• Data Science: Computational Thinking with Python from University of California, Berkeley ★★★★★(2)
• Advanced Data Structures in Java from University of California, San Diego ★★★★☆(2)
• Introduction to Machine Learning from Duke University ★★★★☆(2)
• Human-Computer Interaction IV: Evaluation, Agile Methods & Beyond from Georgia Institute of Technology ★★★★★(2)
• Programming Languages, Part C from University of Washington ★★★★☆(2)
• Data Analytics Foundations for Accountancy I from University of Illinois at Urbana-Champaign ★☆☆☆☆(2)
• Object-Oriented Data Structures in C++ from University of Illinois at Urbana-Champaign ★★★★☆(2)
• Responsive Website Tutorial and Examples from University of London International Programmes ★★★★★(2)
• How to Code: Complex Data from The University of British Columbia ★★★★★(2)
• Fundamentals of Visualization with Tableau from University of California, Davis ★★★★☆(2)
• Algorithms from Indian Institute of Technology Bombay ★★★★★(2)
• Software Testing Management from University System of Maryland ★★☆☆☆(2)
• Web Application Development: Basic Concepts from University of New Mexico ★★★★★(2)
• Client-Server Communication from Google ★★★★★(2)
• Introduction to Computation Theory from Santa Fe Institute ★★★★★(2)
• Developing International Software, Part 1 from Microsoft ★★★★☆(2)
• Principles of Machine Learning from Microsoft ★★★★★(2)
• Data, Analytics, and Learning from University of Texas Arlington ★★☆☆☆(2)
• Fundamentals of Machine Learning in Finance from New York University (NYU) ★★☆☆☆(2)
• Autonomous Mobile Robots from ETH Zurich ★★★★★(2)
• Knowledge Management and Big Data in Business from Hong Kong Polytechnic University ★★★★☆(2)
• Approximation Algorithms Part I from École normale supérieure ★★★★★(2)
• Introduction to Process Mining with ProM from Eindhoven University of Technology ★★★★☆(2)
• HTML5 Apps and Games from World Wide Web Consortium (W3C) ★★☆☆☆(2)
• Intro to Theoretical Computer Science
• Compilers from Stanford University ★★★★★(1)
• Graph Search, Shortest Paths, and Data Structures from Stanford University ★☆☆☆☆(1)
• Computation Structures 2: Computer Architecture from Massachusetts Institute of Technology ★★★★☆(1)
• Computational Thinking for Modeling and Simulation from Massachusetts Institute of Technology ★★☆☆☆(1)
• Advanced Algorithms and Complexity from University of California, San Diego ★★★☆☆(1)
• Advanced R Programming from Johns Hopkins University ★★★★☆(1)
• Advanced Linear Models for Data Science 2: Statistical Linear Models from Johns Hopkins University ★★★★★(1)
• Foundations of Healthcare Systems Engineering from Johns Hopkins University ★★★★★(1)
• Programming for the Internet of Things Project from University of California, Irvine ★★★★☆(1)
• Intro to Analytic Thinking, Data Science, and Data Mining from University of California, Irvine ★★★★★(1)
• Basic Data Processing and Visualization from University of California, San Diego ★★★☆☆(1)
• Database Systems Concepts & Design from Georgia Institute of Technology ★★★★☆(1)
• Human-Computer Interaction III: Ethics, Needfinding & Prototyping from Georgia Institute of Technology ★★★★★(1)
• Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms from Georgia Institute of Technology ★★★★★(1)
• Blockchain Basics from University at Buffalo ★★☆☆☆(1)
• Mathematics for Computer Science from University of London International Programmes ★★★★★(1)
• Software Construction: Data Abstraction from The University of British Columbia ★★★☆☆(1)
• Software Construction: Object-Oriented Design from The University of British Columbia ★★☆☆☆(1)
• DevOps Culture and Mindset from University of California, Davis ★★★★★(1)
• Software Development Processes and Methodologies from University of Minnesota ★★★☆☆(1)
• Server-side Development with NodeJS, Express and MongoDB from The Hong Kong University of Science and Technology ★★★★★(1)
• Essential Linear Algebra for Data Science from University of Colorado Boulder ★★★★☆(1)
• Data Analysis: Visualization and Dashboard Design from Delft University of Technology ★★★☆☆(1)
• Automated Software Testing: Unit Testing, Coverage Criteria and Design for Testability from Delft University of Technology ★★★★☆(1)
• Automated Software Testing: Model and State-based Testing from Delft University of Technology ★★★★★(1)
• Fundamentals of Network Communication from University of Colorado System ★★★★★(1)
• Linux Server Management and Security from University of Colorado System ★★★☆☆(1)
• Hacking and Patching from University of Colorado System ★★★★★(1)
• Formal Software Verification from University System of Maryland ★★☆☆☆(1)
• Software Architecture for the Internet of Things from EIT Digital ★★★★☆(1)
• Paradigms of Computer Programming from Université catholique de Louvain ★★★★☆(1)
• Client-based Web Applications development: ReactJS & Angular from Universidad Politécnica de Madrid ★☆☆☆☆(1)
• Advanced Algorithmics and Graph Theory with Python from Institut Mines-Télécom ★★★★★(1)
• Browser Rendering Optimization from Google ★★★★☆(1)
• Google Maps APIs from Google ★★★★★(1)
• Cybersecurity and Mobility from University System of Georgia ★☆☆☆☆(1)
• Developing SQL Databases from Microsoft ★★☆☆☆(1)
• Introduction to TypeScript 2 from Microsoft ★☆☆☆☆(1)
• Building Interactive Prototypes using JavaScript from Microsoft ★★★★☆(1)
• Introduction to C# from Microsoft ★☆☆☆☆(1)
• Algorithms and Data Structures from Microsoft ★★☆☆☆(1)
• Algorithms and Data Structures in C# from Microsoft ★★★★★(1)
• 2D Game Development with libGDX from Amazon ★★★★★(1)
• Overview of Advanced Methods of Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(1)
• Advanced Database Queries from New York University (NYU) ★★★★★(1)
• Advanced Database Administration from New York University (NYU) ★★★★★(1)
• Introduction to Cloud Infrastructure Technologies from Linux Foundation ★★★★☆(1)
• 用Python玩转数据 Data Processing Using Python from Nanjing University ★★★★★(1)
• Data Processing Using Python from Nanjing University ★★★☆☆(1)
• Fundamentals of Parallelism on Intel Architecture from Intel ★★★★★(1)
• An Introduction to Practical Deep Learning from Intel ★★★☆☆(1)
• How to Win Coding Competitions: Secrets of Champions from ITMO University ★★★☆☆(1)
• Hacker101 from HackerOne ★★★★★(1)
• Diseño de Sistemas de información gerencial para Internet con MySQL / PHP y Joomla from Universidad del Rosario ★★★★★(1)
• Technical Interview from Pramp ★★★★★(1)
• Designing RESTful APIs
• MongoDB for Javascript Developers
• Quantitative Methods for Biology from Harvard University
• Fundamentals of TinyML from Harvard University
• Probabilistic Graphical Models 3: Learning from Stanford University
• Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming from Stanford University
• Shortest Paths Revisited, NP-Complete Problems and What To Do About Them from Stanford University
• Algorithms: Design and Analysis, Part 1 from Stanford University
• Algorithms: Design and Analysis, Part 2 from Stanford University
• Mobile Application Experiences Part 3: Building Mobile Apps from Massachusetts Institute of Technology
• Advanced Software Construction in Java from Massachusetts Institute of Technology
• Mobile Application Experiences from Massachusetts Institute of Technology
• Machine Learning for Healthcare from Massachusetts Institute of Technology
• Data Structures and Software Design from University of Pennsylvania
• Algorithm Design and Analysis from University of Pennsylvania
• Data Analysis Using Python from University of Pennsylvania
• Building Web Applications in Django from University of Michigan
• Django Features and Libraries from University of Michigan
• Web Application Technologies and Django from University of Michigan
• Building Web Applications in Django from University of Michigan
• Django Features and Libraries from University of Michigan
• Developing AR/VR/MR/XR Apps with WebXR, Unity & Unreal from University of Michigan
• Intro to AR/VR/MR/XR: Technologies, Applications & Issues from University of Michigan
• Introduction to Machine Learning in Sports Analytics from University of Michigan
• Database Architecture, Scale, and NoSQL with Elasticsearch from University of Michigan
• Introduction to Neurohacking In R from Johns Hopkins University
• Building Data Visualization Tools from Johns Hopkins University
• Exploratory Data Analysis from Johns Hopkins University
• The Merkle Tree and Cryptocurrencies from University of California, Irvine
• Data Science: Machine Learning and Predictions from University of California, Berkeley
• Blockchain Technology from University of California, Berkeley
• Data, Models and Decisions in Business Analytics from Columbia University
• Internet of Things: Sensing and Actuation From Devices from University of California, San Diego
• Minecraft, Coding and Teaching from University of California, San Diego
• How Virtual Reality Works from University of California, San Diego
• Introduction to Genomic Data Science from University of California, San Diego
• Data Structures Fundamentals from University of California, San Diego
• Graph Algorithms from University of California, San Diego
• String Processing and Pattern Matching Algorithms from University of California, San Diego
• Computer Science: Algorithms, Theory, and Machines from Princeton University
• Java Programming: Build a Recommendation System from Duke University
• Cloud Data Engineering from Duke University
• Cloud Virtualization, Containers and APIs from Duke University
• Machine Learning Foundations for Product Managers from Duke University
• Managing Machine Learning Projects from Duke University
• Web Applications and Command-Line Tools for Data Engineering from Duke University
• Human-Computer Interaction from Georgia Institute of Technology
• Software Analysis & Testing from Georgia Institute of Technology
• Introduction to Graduate Algorithms from Georgia Institute of Technology
• Network Function Virtualization from Georgia Institute of Technology
• Cloud Systems Software from Georgia Institute of Technology
• Cloud Applications from Georgia Institute of Technology
• Cybersecurity: The CISO’s View from University of Washington
• Building a Cybersecurity Toolkit from University of Washington
• Finding Your Cybersecurity Career Path from University of Washington
• Machine Teaching for Autonomous AI from University of Washington
• Designing Autonomous AI from University of Washington
• Building Autonomous AI from University of Washington
• Data Analytics Foundations for Accountancy II from University of Illinois at Urbana-Champaign
• Data Modeling and Regression Analysis in Business from University of Illinois at Urbana-Champaign
• Unordered Data Structures from University of Illinois at Urbana-Champaign
• Ordered Data Structures from University of Illinois at Urbana-Champaign
• Machine Learning for Accounting with Python from University of Illinois at Urbana-Champaign
• Machine Learning Algorithms with R in Business Analytics from University of Illinois at Urbana-Champaign
• Advanced Deep Learning Methods for Healthcare from University of Illinois at Urbana-Champaign
• Blockchain Platforms from University at Buffalo
• Smart Contracts from University at Buffalo
• Decentralized Applications (Dapps) from University at Buffalo
• Data Analysis and Visualization from University at Buffalo
• Supercomputing from Partnership for Advanced Computing in Europe
• Introduction to Predictive Analytics using Python from University of Edinburgh
• Foundations of Data Science: K-Means Clustering in Python from University of London International Programmes
• Introduction to Applied Cryptography from University of London International Programmes
• Implementation Strategies: AI and Cognitive Computing from The University of British Columbia
• Implementation Strategies: Cloud Computing from The University of British Columbia
• Worldbuilding for Video Games from The University of British Columbia
• Creating Dashboards and Storytelling with Tableau from University of California, Davis
• Essential Design Principles for Tableau from University of California, Davis
• Continuous Integration from University of California, Davis
• Data Wrangling, Analysis and AB Testing with SQL from University of California, Davis
• Identifying Security Vulnerabilities in C/C++Programming from University of California, Davis
• Exploiting and Securing Vulnerabilities in Java Applications from University of California, Davis
• Distributed Computing with Spark SQL from University of California, Davis
• Game Design and Development 3: 3D Shooter from Michigan State University
• Game Design and Development 2: 2D Platformer from Michigan State University
• Game Design and Development 1: 2D Shooter from Michigan State University
• Game Design and Development 4: 3D Platformer from Michigan State University
• Moving to the Cloud from University of Melbourne
• Signals, Systems, and Learning from Rice University
• Bioinformatics: Introduction and Methods 生物信息学: 导论与方法 from Peking University
• 面向对象技术高级课程（The Advanced Object-Oriented Technology） from Peking University
• 操作系统与虚拟化安全 from Peking University
• 计算机组成 Computer Organization from Peking University
• 计算机辅助翻译原理与实践 Principles and Practice of Computer-Aided Translation from Peking University
• 数据结构基础 from Peking University
• 高级数据结构与算法 from Peking University
• 操作系统原理（Operating Systems） from Peking University
• 算法设计与分析 Design and Analysis of Algorithms from Peking University
• 算法基础 from Peking University
• 算法设计与分析(高级) | Advanced Design and Analysis of Algorithms from Peking University
• Java程序设计 from Peking University
• LAFF – On Programming for Correctness from The University of Texas at Austin
• Lean Software Development from University of Minnesota
• Engineering Practices for Building Quality Software from University of Minnesota
• Introduction to Automated Analysis from University of Minnesota
• Web and Mobile Testing with Selenium from University of Minnesota
• Black-box and White-box Testing from University of Minnesota
• Front-End Web UI Frameworks and Tools: Bootstrap 4 from The Hong Kong University of Science and Technology
• Mathematical Methods for Data Analysis from The Hong Kong University of Science and Technology
• Software Engineering: Modeling Software Systems using UML from The Hong Kong University of Science and Technology
• Software Engineering: Implementation and Testing from The Hong Kong University of Science and Technology
• Software Engineering: Software Design and Project Management from The Hong Kong University of Science and Technology
• Big Data for Reliability and Security from Purdue University
• Introduction to Deep Learning from Purdue University
• Dealing With Missing Data from University of Maryland, College Park
• Project Planning and Machine Learning from University of Colorado Boulder
• Algorithms for Searching, Sorting, and Indexing from University of Colorado Boulder
• Dynamic Programming, Greedy Algorithms from University of Colorado Boulder
• Data Mining Methods from University of Colorado Boulder
• Fundamentals of Software Architecture for Big Data from University of Colorado Boulder
• Advanced Topics and Future Trends in Database Technologies from University of Colorado Boulder
• Applications of Software Architecture for Big Data from University of Colorado Boulder
• Software Architecture Patterns for Big Data from University of Colorado Boulder
• Data Analysis: Building Your Own Business Dashboard from Delft University of Technology
• Global Software Development from Delft University of Technology
• Fundamentals of Quantum Information from Delft University of Technology
• Homeland Security & Cybersecurity Connection – It’s Not About the Terrorists from University of Colorado System
• Peer-to-Peer Protocols and Local Area Networks from University of Colorado System
• Packet Switching Networks and Algorithms from University of Colorado System
• Detecting and Mitigating Cyber Threats and Attacks from University of Colorado System
• Design and Analyze Secure Networked Systems from University of Colorado System
• Basic Cryptography and Programming with Crypto API from University of Colorado System
• Asymmetric Cryptography and Key Management from University of Colorado System
• Symmetric Cryptography from University of Colorado System
• Software Design Threats and Mitigations from University of Colorado System
• Requirements Specifications: Goals and Conflict Analysis from University of Colorado System
• SRS Documents: Requirements and Diagrammatic Notations from University of Colorado System
• Requirements Gathering for Secure Software Development from University of Colorado System
• Software Requirements Prioritization: Risk Analysis from University of Colorado System
• Requirements Elicitation: Artifact and Stakeholder Analysis from University of Colorado System
• Data Structures and Design Patterns for Game Developers from University of Colorado System
• Cloud Computing Security from University of Colorado System
• Advanced System Security Topics from University of Colorado System
• Algorithms, Data Collection, and Starting to Code from University of Colorado System
• Data Analysis and Representation, Selection and Iteration from University of Colorado System
• Implementation of Data Structures from Indian Institute of Technology Bombay
• Foundations of Data Structures from Indian Institute of Technology Bombay
• I sistemi Operativi Moderni from University of Naples Federico II
• Nuove tecnologie digitali from University of Naples Federico II
• Laboratorio di programmazione: strumenti e programmi from University of Naples Federico II
• NoSQL systems from Universidad Nacional Autónoma de México
• Designing data-intensive applications from Universidad Nacional Autónoma de México
• Relational database systems from Universidad Nacional Autónoma de México
• Cognición encarnada from Universidad Nacional Autónoma de México
• Software Testing Fundamentals from University System of Maryland
• Data Structures and Algorithm Design Part I | 数据结构与算法设计(上) from Tsinghua University
• Data Structures and Algorithms (I) from Tsinghua University
• Data Structures and Algorithms (II) from Tsinghua University
• Data Structures and Algorithms (III) from Tsinghua University
• Data Structures and Algorithms (IV) from Tsinghua University
• Algoritmos y Programación en R from Tecnológico de Monterrey
• Enterprise Software Lifecycle Management from National Research Nuclear University MEPhI
• Data Processing and Analysis with Excel from Rochester Institute of Technology
• Data Representation and Visualization in Tableau from Rochester Institute of Technology
• Getting Started with Unreal Engine from Rochester Institute of Technology
• Artificial Intelligence: An Overview from Politecnico di Milano
• Machine Learning: an overview from Politecnico di Milano
• The Software Architect Code: Building the Digital World from Universidad Carlos iii de Madrid
• Introduction to Java Programming: Fundamental Data Structures and Algorithms from Universidad Carlos iii de Madrid
• Introduction to Architecting Smart IoT Devices from EIT Digital
• Architecting Smart IoT Devices from EIT Digital
• I/O-efficient algorithms from EIT Digital
• Reviews & Metrics for Software Improvements from University of Alberta
• Cybersecurity and Privacy in the IoT from Curtin University
• Communicating with Robots and Bots from Curtin University
• Understanding Artificial Intelligence through Algorithmic Information Theory from Institut Mines-Télécom
• Procedural Modelling from National University of Singapore
• Using Machine Learning in Trading and Finance from New York Institute of Finance
• Introdução ao Teste de Software from Universidade de São Paulo
• Intro to Data Structures and Algorithms from Google
• Offline Web Applications from Google
• Intro to Progressive Web Apps from Google
• Introduction to Data Structures from University of Adelaide
• Programming for Data Science from University of Adelaide
• Cybersecurity and the X-Factor from University System of Georgia
• Cybersecurity and the Internet of Things from University System of Georgia
• Programming in R for Data Science from Microsoft
• Developing Intelligent Apps and Bots from Microsoft
• Applied Machine Learning from Microsoft
• AngularJS: Framework Fundamentals from Microsoft
• Implementing In-Memory SQL Database Objects from Microsoft
• Building Functional Prototypes using Node.js from Microsoft
• Application Design Considerations: An Inclusive Approach from Microsoft
• Designing Data Platform Solutions from Microsoft
• Network Security & Database Vulnerabilities from IBM
• Cybersecurity Compliance Framework & System Administration from IBM
• Real-Time Cyber Threat Detection and Mitigation from New York University (NYU)
• Enterprise and Infrastructure Security from New York University (NYU)
• Information Security – Introduction to Information Security from New York University (NYU)
• Information Security – Advanced topics from New York University (NYU)
• Penetration Testing – Discovering Vulnerabilities from New York University (NYU)
• Penetration Testing – Post Exploitation from New York University (NYU)
• Quantum Computer Systems Design I: Intro to Quantum Computation and Programming from The University of Chicago
• Quantum Computer Systems Design II: Principles of Quantum Architecture from The University of Chicago
• Quantum Computer Systems Design III: Working with Noisy Systems from The University of Chicago
• Blockchain Scalability and its Foundations in Distributed Systems from The University of Sydney
• Introduction to DevOps: Transforming and Improving Operations from Linux Foundation
• Introduction to Kubernetes from Linux Foundation
• Business Considerations for 5G with Edge, IoT, and AI from Linux Foundation
• Open Source and the 5G Transition from Linux Foundation
• Introduction to Serverless on Kubernetes from Linux Foundation
• Web App Development with the Power of Node.js from Technische Universität München (Technical University of Munich)
• IoT System Architecture: Design and Evaluation from Waseda University
• UML Class Diagrams for Software Engineering from KU Leuven University
• Data Science in the Games Industry from University of Dundee
• Internet of Things for Active Ageing from Taipei Medical University
• Orientação a Objetos com Java from Instituto Tecnológico de Aeronáutica
• Computer Architecture from Harvey Mudd College
• More Data Mining with Weka from University of Waikato
• Introduction: Elements of Microgame Design from Worcester Polytechnic Institute
• Using R for Regression and Machine Learning in Investment from Sungkyunkwan University
• Mejora tu Negocio con Inteligencia Artificial from Universidad Anáhuac
• Defensive Programming and Debugging from Partnership for Advanced Computing in Europe
• Python in High Performance Computing from Partnership for Advanced Computing in Europe
• Concurrency from AdaCore University
• Introduction to Applied Machine Learning from Alberta Machine Intelligence Institute
• Bias and Discrimination in AI from Université de Montréal
• Deep Learning Essentials from Université de Montréal
• Code of Life – When Computer Science Meets Genetics
• Dynamic Web Applications with Sinatra
• Deploying Applications with Heroku
• VR Scenes and Objects
• MongoDB for Python Developers

Сеньор

• The Analytics Edge from Massachusetts Institute of Technology ★★★★★(80)
• Machine Learning Foundations: A Case Study Approach from University of Washington ★★★★☆(40)
• Sample-based Learning Methods from University of Alberta ★★★★★(40)
• Computer Simulations from University of California, Davis ★★★★★(38)
• Introducción al diseño de hardware con Verilog from Galileo University ★★★★★(38)
• Introduction to Artificial Intelligence from Stanford University ★★★★☆(27)
• [New] Machine Learning for Computer Vision from MathWorks
• Fundamentals of Reinforcement Learning from University of Alberta ★★★★★(24)
• Pattern Discovery in Data Mining from University of Illinois at Urbana-Champaign ★★☆☆☆(21)
• Machine Learning: Regression from University of Washington ★★★★★(20)
• Statistical Thinking for Data Science and Analytics from Columbia University ★★☆☆☆(19)
• Bitcoin and Cryptocurrency Technologies from Princeton University ★★★★☆(19)
• Prediction and Control with Function Approximation from University of Alberta ★★★★★(19)
• Probabilistic Graphical Models 1: Representation from Stanford University ★★★★☆(18)
• Developing Data Products from Johns Hopkins University ★★★★☆(18)
• Finding Hidden Messages in DNA (Bioinformatics I) from University of California, San Diego ★★★★★(17)
• Neural Networks and Deep Learning from DeepLearning.AI ★★★★★(15)
• Machine Learning for Data Science and Analytics from Columbia University ★★★☆☆(15)
• Machine Learning With Big Data from University of California, San Diego ★★☆☆☆(14)
• Artificial Intelligence (AI) from Columbia University ★★★★☆(12)
• Machine Learning from Columbia University ★★★★☆(12)
• Text Mining and Analytics from University of Illinois at Urbana-Champaign ★★★★☆(10)
• Hardware Security from University of Maryland, College Park ★★★☆☆(10)
• Applied Plotting, Charting & Data Representation in Python from University of Michigan ★★☆☆☆(9)
• Machine Learning: Classification from University of Washington ★★★★★(9)
• Mathematics for Machine Learning: Multivariate Calculus from Imperial College London ★★★★★(9)
• Convolutional Neural Networks from DeepLearning.AI ★★★★★(8)
• Reinforcement Learning from Brown University ★★★☆☆(8)
• Practical Deep Learning For Coders from fast.ai ★★★★☆(8)
• Cluster Analysis in Data Mining from University of Illinois at Urbana-Champaign ★★★☆☆(7)
• Structuring Machine Learning Projects from DeepLearning.AI ★★★★☆(6)
• Applied Machine Learning in Python from University of Michigan ★★★★☆(6)
• Enabling Technologies for Data Science and Analytics: The Internet of Things from Columbia University ★☆☆☆☆(6)
• Graph Analytics for Big Data from University of California, San Diego ★★★☆☆(6)
• Machine Learning from Georgia Institute of Technology ★★★★☆(6)
• Advanced Operating Systems from Georgia Institute of Technology ★★★★★(6)
• Interactive 3D Graphics from Autodesk ★★★★☆(6)
• Model Building and Validation from AT&T ★★☆☆☆(6)
• Machine Learning: Clustering & Retrieval from University of Washington ★★★★★(5)
• Applied Cryptography from University of Virginia ★★★★☆(5)
• Introduction to Computer Architecture from Carnegie Mellon University ★★★★★(5)
• Sparse Representations in Image Processing: From Theory to Practice from Technion – Israel Institute of Technology ★★★★★(5)
• Genome Sequencing (Bioinformatics II) from University of California, San Diego ★★★★★(4)
• Machine Learning for Data Analysis from Wesleyan University ★★★★☆(4)
• Probabilistic Graphical Models 2: Inference from Stanford University ★★★★☆(3)
• Applied Social Network Analysis in Python from University of Michigan ★★★★☆(3)
• Practical Predictive Analytics: Models and Methods from University of Washington ★★☆☆☆(3)
• Regression Modeling in Practice from Wesleyan University ★★★★☆(3)
• Mathematics for Machine Learning: PCA from Imperial College London ★★☆☆☆(3)
• Quantitative Formal Modeling and Worst-Case Performance Analysis from EIT Digital ★★★☆☆(3)
• Comparing Genes, Proteins, and Genomes (Bioinformatics III) from University of California, San Diego ★★★★★(2)
• Genomic Data Science and Clustering (Bioinformatics V) from University of California, San Diego ★★★★☆(2)
• Knowledge-Based AI: Cognitive Systems from Georgia Institute of Technology ★★★☆☆(2)
• Introduction to Operating Systems from Georgia Institute of Technology ★★★★★(2)
• Intro to Information Security from Georgia Institute of Technology ★★☆☆☆(2)
• Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud from University of Illinois at Urbana-Champaign ★★★☆☆(2)
• Foundations of Data Analysis – Part 2: Inferential Statistics from The University of Texas at Austin ★★★★☆(2)
• Introduction to Deep Learning from Higher School of Economics ★★★☆☆(2)
• Nearest Neighbor Collaborative Filtering from University of Minnesota ★★☆☆☆(2)
• Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘：理论与算法 from Tsinghua University ★★★☆☆(2)
• Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(2)
• Real-Time Analytics with Apache Storm from Twitter ★★★★☆(2)
• Advanced Linear Models for Data Science 1: Least Squares from Johns Hopkins University ★★★★★(1)
• Artificial Intelligence for Breast Cancer Detection from Johns Hopkins University ★★★★☆(1)
• High Performance Computer Architecture from Georgia Institute of Technology ★★★★★(1)
• Computational Photography from Georgia Institute of Technology ★★★★☆(1)
• Computability, Complexity & Algorithms from Georgia Institute of Technology ★★★★★(1)
• Network Security from Georgia Institute of Technology ★★★★★(1)
• Big Data, Genes, and Medicine from State University of New York ★★★★☆(1)
• Quantum Machine Learning from University of Toronto ★★★★★(1)
• Parallel Programming in Java from Rice University ★★★★☆(1)
• Concurrent Programming in Java from Rice University ★★★★★(1)
• Relational Database Support for Data Warehouses from University of Colorado System ★★☆☆☆(1)
• Big Data Analysis with Scala and Spark from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
• Nature, in Code: Biology in JavaScript from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
• Hands-on Text Mining and Analytics from Yonsei University ★★★★★(1)
• Optimize ML Models and Deploy Human-in-the-Loop Pipelines from DeepLearning.AI ★★★★☆(1)
• DevOps Practices and Principles from Microsoft ★★☆☆☆(1)
• Deep Learning and Reinforcement Learning from IBM ★★★☆☆(1)
• Introduction to Cloud Foundry and Cloud Native Software Architecture from Linux Foundation ★★★★★(1)
• Sparse Representations in Signal and Image Processing: Fundamentals from Technion – Israel Institute of Technology ★★★★★(1)
• AI for Medical Diagnosis from DeepLearning.AI ★★★★☆(1)
• Big Data Science with the BD2K-LINCS Data Coordination and Integration Center from Icahn School of Medicine at Mount Sinai ★★★★☆(1)
• Security Operations and Administration from (ISC)² ★★★★★(1)
• Systems and Application Security from (ISC)² ★★★★☆(1)
• Identifying, Monitoring, and Analyzing Risk and Incident Response and Recovery from (ISC)² ★★★★☆(1)
• Principles, Statistical and Computational Tools for Reproducible Data Science from Harvard University
• Unsupervised Learning, Recommenders, Reinforcement Learning from DeepLearning.AI
• Advanced Learning Algorithms from DeepLearning.AI
• Real-Time Audio Signal Processing in Faust from Stanford University
• Computation Structures 3: Computer Organization from Massachusetts Institute of Technology
• Number Theory and Cryptography from University of California, San Diego
• Introduction to Concurrent Programming with GPUs from Johns Hopkins University
• Cryptography and Hashing Overview from University of California, Irvine
• Predictive Modeling, Model Fitting, and Regression Analysis from University of California, Irvine
• Cluster Analysis, Association Mining, and Model Evaluation from University of California, Irvine
• Data Science: Inferential Thinking through Simulations from University of California, Berkeley
• Molecular Evolution (Bioinformatics IV) from University of California, San Diego
• Finding Mutations in DNA and Proteins (Bioinformatics VI) from University of California, San Diego
• Dynamic Programming: Applications In Machine Learning and Genomics from University of California, San Diego
• NP-Complete Problems from University of California, San Diego
• Design Thinking and Predictive Analytics for Data Products from University of California, San Diego
• Deploying Machine Learning Models from University of California, San Diego
• Meaningful Predictive Modeling from University of California, San Diego
• High Performance Computing from Georgia Institute of Technology
• GT – Refresher – Advanced OS from Georgia Institute of Technology
• Artificial Intelligence from Georgia Institute of Technology
• Cyber-Physical Systems Security from Georgia Institute of Technology
• Compilers: Theory and Practice from Georgia Institute of Technology
• FA17: Machine Learning from Georgia Institute of Technology
• Machine Learning from Georgia Institute of Technology
• Cyber-Physical Systems Design & Analysis from Georgia Institute of Technology
• Predictive Analytics using Machine Learning from University of Edinburgh
• Plant Bioinformatics from University of Toronto
• Advanced Modeling for Discrete Optimization from University of Melbourne
• Basic Modeling for Discrete Optimization from University of Melbourne
• 离散优化建模基础篇 Basic Modeling for Discrete Optimization from The Chinese University of Hong Kong
• 离散优化建模高阶篇 Advanced Modeling for Discrete Optimization from The Chinese University of Hong Kong
• 离散优化算法篇 Solving Algorithms for Discrete Optimization from The Chinese University of Hong Kong
• Solving Algorithms for Discrete Optimization from University of Melbourne
• Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions from Rice University
• Quantum Cryptography from California Institute of Technology
• LAFF-On Programming for High Performance from The University of Texas at Austin
• Machine Learning from The University of Texas at Austin
• Обработка изображений from Higher School of Economics
• Introduction to Recommender Systems: Non-Personalized and Content-Based from University of Minnesota
• Recommender Systems: Evaluation and Metrics from University of Minnesota
• Matrix Factorization and Advanced Techniques from University of Minnesota
• Computer Applications of Artificial Intelligence and e-Construction from Purdue University
• Combining and Analyzing Complex Data from University of Maryland, College Park
• Introduction to High-Performance and Parallel Computing from University of Colorado Boulder
• Statistical Inference for Estimation in Data Science from University of Colorado Boulder
• Classical Cryptosystems and Core Concepts from University of Colorado System
• Mathematical Foundations for Cryptography from University of Colorado System
• Cryptographic Hash and Integrity Protection from University of Colorado System
• Cryptography and Information Theory from University of Colorado System
• MATLAB et Octave pour débutants from École Polytechnique Fédérale de Lausanne
• Optimization: principles and algorithms – Linear optimization from École Polytechnique Fédérale de Lausanne
• Optimization: principles and algorithms – Network and discrete optimization from École Polytechnique Fédérale de Lausanne
• Optimization: principles and algorithms – Unconstrained nonlinear optimization from École Polytechnique Fédérale de Lausanne
• Il linguaggio naturale, dall’uomo alla macchina from University of Naples Federico II
• Machine Learning e Data Mining in R from University of Naples Federico II
• 機器學習基石下 (Machine Learning Foundations)—Algorithmic Foundations from National Taiwan University
• 人工智慧：搜尋方法與邏輯推論 (Artificial Intelligence – Search & Logic) from National Taiwan University
• 人工智慧：機器學習與理論基礎 (Artificial Intelligence – Learning & Theory) from National Taiwan University
• Operations Research (1): Models and Applications from National Taiwan University
• Operations Research (2): Optimization Algorithms from National Taiwan University
• Sesenta años de inteligencia artificial from Universidad Nacional Autónoma de México
• Razonamiento artificial from Universidad Nacional Autónoma de México
• DNA Sequences: Alignments and Analysis from University System of Maryland
• 计算几何 | Computational Geometry from Tsinghua University
• Big Data Machine Learning | 大数据机器学习 from Tsinghua University
• System Validation: Automata and behavioural equivalences from EIT Digital
• System Validation (2): Model process behaviour from EIT Digital
• System Validation (4): Modelling Software, Protocols, and other behaviour from EIT Digital
• System Validation (3): Requirements by modal formulas from EIT Digital
• Approximation Algorithms from EIT Digital
• Automated Reasoning: Symbolic Model Checking from EIT Digital
• Generative Modelling from National University of Singapore
• Performative Modelling from National University of Singapore
• Infrastructure as Code from Microsoft
• DevOps Testing from Microsoft
• DevOps for Databases from Microsoft
• Secure Software Development: Verification and More Specialized Topics from Linux Foundation
• Secure Software Development: Requirements, Design, and Reuse from Linux Foundation
• Introduction to RISC-V from Linux Foundation
• Building a RISC-V CPU Core from Linux Foundation
• RISC-V Toolchain and Compiler Optimization Techniques from Linux Foundation
• Cyber-Physical Systems: Modeling and Simulation from University of California, Santa Cruz
• Introduction to Statistical Methods for Gene Mapping from Kyoto University
• AI for Medical Prognosis from DeepLearning.AI
• AI For Medical Treatment from DeepLearning.AI
• Build Basic Generative Adversarial Networks (GANs) from DeepLearning.AI
• Build Better Generative Adversarial Networks (GANs) from DeepLearning.AI
• Apply Generative Adversarial Networks (GANs) from DeepLearning.AI
• Generative Deep Learning with TensorFlow from DeepLearning.AI
• Custom Models, Layers, and Loss Functions with TensorFlow from DeepLearning.AI
• Deploying Machine Learning Models in Production from DeepLearning.AI
• Machine Learning Modeling Pipelines in Production from DeepLearning.AI
• Machine Learning Data Lifecycle in Production from DeepLearning.AI
• Introduction to Machine Learning in Production from DeepLearning.AI
• Computer System Design: Advanced Concepts of Modern Microprocessors from Chalmers University of Technology
• Approximation Algorithms Part II from École normale supérieure
• Reliable Distributed Algorithms – Part 2 from KTH Royal Institute of Technology
• Access Controls from (ISC)²
• Networks and Communications Security from (ISC)²
• Optimizing Machine Learning Performance from Alberta Machine Intelligence Institute