Online Open Education

Opne online education Below is a comprehensive list of computer science online introductory courses which you can use to get introduced with the various subject in computing , as well as to increase the level of knowledge in this area.

Computer Science

Computer Science 101 (Stanford University) Networks Illustrated: Principles without Calculus (Princeton University) Internet History, Technology, and Security (University of Michigan)


Learn to Program: The Fundamentals (University of Toronto) Learn to Program: Crafting Quality Code (University of Toronto) An Introduction to Interactive Programming in Python (Rice University) Introduction to Computer Science (University of Virginia) Programming for Everybody (University of Michigan)


Introduction to Algebra (Wake Technical Community College) College Algebra (San Jose State University) * Visualizing Algebra (San Jose State University) Intermediate Algebra (University of California, Irvine) Pre-Calculus (University of California, Irvine) Calculus One (The Ohio State University) * Calculus Two: Sequences and Series (The Ohio State University) * Calculus: Single Variable (The Ohio State University) * Multivariable Differential Calculus (The Ohio State University) * Introduction to Mathematical Thinking (Stanford University) * Real estate mathematics and financial literacy Introduction to Physics (Udacity University)

General Courses


Mathematics for Computer Science (MIT) * Introduction to Logic (Stanford University) * Logic: Language and Information 1 (The University of Melbourne) Logic: Language and Information 2 (The University of Melbourne) Automata (Stanford University) *  

Probability and Statistics

Statistics: Making Sense of Data (University of Toronto) Introduction to Statistics (Stanford University) * Statistics One (Princeton University) * Statistics (San Jose State University) Mathematical Biostatistics (John Hopkins)

Algorithms and data structure

Algorithms, Part I (Princeton University) * Algorithms, Part II (Princeton University) * Algorithms: Design and Analysis, Part 1 (Stanford University) Algorithms: Design and Analysis, Part 2 (Stanford University) Algorithms (Rutgers University) Introduction to Theoretical Computer Science (Universität Tübingen) Introduction to Algorithms (MIT)

Data bases

Introduction to Databases (Stanford University) * Database Systems (MIT)  

Software Programming

Introduction to Programming (San Jose State University) Introduction to Object Oriented Programming (Udacity University) Design of Computer Programs (Google) * Web Development (Reddit) * Software Testing (University of Utah) Software Debugging (Saarland University) Startup Engineering (Stanford University)  

Computer Architecture

Computer Architecture ( The Hardware/Software Interface (University of Washington) Computer Architecture (Carnegie Mellon University) Computer Architecture (Princeton University)  

Operating Systems

Operating Systems (University of California, Berkeley)  


Computer Networks (University of Washington) * Introduction to Computer Networking (Stanford University) * Introduction to Data Communications (Thammasat University) Software Defined Networking (Georgia Institute of Technology)



Algorithms and Optimisation

Analysis of Algorithms (Princeton University) Advanced Data Structures (MIT) * Discrete Optimisation (The University of Melbourne) Linear and Discrete Optimisation (EPFL) Linear and Integer Programming (University of Colorado) Convex Optimisation (Stanford University)  

Artificial Intelligence

Introduction to Artificial Intelligence (Google) * Artificial Intelligence Planning (University of Edinburgh) Artificial Intelligence for Robotics (Stanford University) Natural Language Processing (Stanford University) * Natural Language Processing (Columbia University) Introduction to Recommender Systems (University of Minnesota) Web Intelligence and Big Data (IIT) Computational Cognitive Science (MIT)  

Statistics and Data Analysis

R Programming (John Hopkins) Data Analysis (John Hopkins) Computing for Data Analysis (John Hopkins) Exploratory Data Analysis (John Hopkins) Statistical Inference (John Hopkins) Regression Models (John Hopkins) Data Analysis and Statistical Inference (Duke University) Core Concepts in Data Analysis (Higher School of Economics) Introduction to Data Science (Airbnb) Exploratory Data Analysis (Facebook) Making Better Group Decisions: Voting, Judgement Aggregation and Fair Division (University of Maryland)  

Machine Learning

Machine Learning (Stanford University) * Machine Learning (University of Washington) Practical Machine Learning (John Hopkins) Neural Networks for Machine Learning (University of Toronto) Machine Learning 1 — Supervised Learning (Georgia Institute of Technology) Machine Learning 2 — Unsupervised Learning (Georgia Institute of Technology) Machine Learning 3 — Reinforcement Learning (Georgia Institute of Technology) Statistical Learning (Stanford University) *

Programming Languages

Programming Languages (University of Washington) Programming Languages (University of Virginia) C++ For C Programmers (University of California, Santa Cruz) Human-Computer Interaction (University of California, San Diego) Compilers (Stanford University) Pattern-Oriented Software Architectures (Vanderbilt University) Mobile Web Development (Google) HTML5 Game Development (Google) Programming Cloud Services for Android Handheld Systems (Vanderbilt University) Web Application Architectures (University of New Mexico) Heterogeneous Parallel Programming (University of Illinois at Urbana-Champaign) Introduction to Point and Click App Development (Salesforce) Introduction to Hadoop and MapReduce (Cloudera) Introduction to Parallel Programming (NVIDIA) Data Wrangling with MongoDB (MongoDB)  

Computer Security and Cryptography

Cryptography I (Stanford University) Cryptography II (Stanford University) Cryptography (University of Maryland) Applied Cryptography (University of Virginia) Introduction to Cryptography (Ruhr University) Computer Security (Stanford University) Usable Security (University of Maryland) Designing and Executing Information Security Strategies (University of Washington) Software Security (University of Maryland) Hardware Security (University of Maryland) Introduction to Forensic Science (Nanyang Technological University, Singapore)  


Tales from the Genome (University of California, San Francisco) Bioinformatics: Life Sciences on Your Computer (Johns Hopkins University) Bioinformatic Methods I (University of Toronto) Bioinformatic Methods II (University of Toronto) Bioinformatics Algorithms (Part 1) (University of California, San Diego) Introduction to Systems Biology (Icahn School of Medicine at Mount Sinai) Network Analysis in Systems Biology (Icahn School of Medicine at Mount Sinai) Dynamical Modelling Methods for Systems Biology (Icahn School of Medicine at Mount Sinai)