# Computer Science - Great Courses

This is a list of high-quality courses that, for one reason or another, didn't make it into the curriculum.
The most common reasons are that the course isn't available often enough,
or that there was an alternative that fit better into the curriculum.

## Programming

Courses | Duration | Effort
:-- | :--: | :--:
[Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-5#!)| 9 weeks | 15 hours/week
[Introduction to Computational Thinking and Data Science](https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-2#!)| 10 weeks | 15 hours/week
[Introduction to Computer Science (Udacity)](https://www.udacity.com/course/intro-to-computer-science--cs101)| 7 weeks | 10-20 hours/week
[An Introduction to Interactive Programming in Python (Part 1)](https://www.coursera.org/learn/interactive-python-1)| 5 weeks | -
[An Introduction to Interactive Programming in Python (Part 2)](https://www.coursera.org/learn/interactive-python-2)| - | -
[Programming Basics](https://www.edx.org/course/programming-basics-iitbombayx-cs101-1x)| 9 weeks | 8 hours/week
[Object-Oriented Programming](https://www.edx.org/course/object-oriented-programming-iitbombayx-cs101-2x)| 4 weeks | 8 hours/week
[Introduction to Programming with MATLAB](https://www.coursera.org/learn/matlab)| - | -
[Introduction to Functional Programming](https://www.edx.org/course/introduction-functional-programming-delftx-fp101x-0)| 7 weeks | 4-6 hours/week

## Math

Courses | Duration | Effort
:-- | :--: | :--:
[Introduction to Probability and Data](https://www.coursera.org/learn/probability-intro)| - | -

## Systems

Courses | Duration | Effort
:-- | :--: | :--:
[Operating System Engineering](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-828-operating-system-engineering-fall-2012/) | - | -
[Introduction to Operating Systems](https://www.udacity.com/course/introduction-to-operating-systems--ud923)| 8 weeks | 5-8 hours/week
[Advanced Operating Systems](https://www.udacity.com/course/advanced-operating-systems--ud189)| 5 weeks | 5-8 hours/week
[Computer Networking](https://www.udacity.com/course/computer-networking--ud436) | 12 weeks | 5-8 hours/week

## Theory

Courses | Duration | Effort
:-- | :--: | :--:
[Algorithms, Part I](https://www.coursera.org/learn/algorithms-part1) | 6 weeks | 6-12 hours/week | some programming
[Algorithms, Part II](https://www.coursera.org/learn/algorithms-part2) | 6 weeks | 6-12 hours/week | Algorithms, Part I
[Analysis of Algorithms (Skiena)](http://www3.cs.stonybrook.edu/~skiena/373/) | 15 weeks | 6-8 hours/week
[Analysis of Algorithms (Sedgewick)](https://www.coursera.org/course/aofa)| 6 weeks | 6-8 hours/week
[Programming Challenges (Skiena)](http://www3.cs.stonybrook.edu/~skiena/392/) | 14 weeks | 6-8 hours/week
[Mathematical Logic and Algorithms Theory](https://iversity.org/en/courses/mathematical-logic-and-algorithms-theory) | 7 weeks | 3-4 hours/week
[Algorithmic Toolbox](https://www.coursera.org/learn/algorithmic-toolbox/) | 5 weeks | 4-8 hours/week
[Algorithms on Graphs and Trees](https://www.coursera.org/learn/algorithms-on-graphs-and-trees/) | - | -
[Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/) | - | -
[Advanced Algorithms and Complexity](https://www.coursera.org/learn/advanced-algorithms-and-complexity/) | - | -
[Algorithmic Thinking (Part 1)](https://www.coursera.org/learn/algorithmic-thinking-1/) | - | -
[Algorithmic Thinking (Part 2)](https://www.coursera.org/learn/algorithmic-thinking-2/) | - | -
[Statistical Mechanics: Algorithms and Computations](https://www.coursera.org/learn/statistical-mechanics/) | - | -
[Approximation Algorithms Part I](https://www.coursera.org/learn/approximation-algorithms-part-1/) | - | -
[Approximation Algorithms Part II](https://www.coursera.org/learn/approximation-algorithms-part-2/) | - | -
[Algorithms: Design and Analysis, Part 1](https://www.coursera.org/course/algo) | 6 weeks | 5-7 hours/week
[Algorithms: Design and Analysis, Part 2](https://www.coursera.org/course/algo2) | 6 weeks | 6-10 hours/week

## Applications

Courses | Duration | Effort
:-- | :--: | :--:
[Web Application Architectures](https://www.coursera.org/course/webapplications)| 6 weeks | 6-9 hours/week
[Agile Development Using Ruby on Rails - Basics](https://www.edx.org/course/agile-development-using-ruby-rails-uc-berkeleyx-cs169-1x)| 9 weeks | 12 hours/week
[Agile Development Using Ruby on Rails - Advanced](https://www.edx.org/course/agile-development-using-ruby-rails-uc-berkeleyx-cs169-2x)| 8 weeks | 12 hours/week
[Startup Engineering](https://www.coursera.org/course/startup) | 12 weeks | 2-20 hours/week
[Using Databases with Python](https://www.coursera.org/learn/python-databases) | 5 weeks | 2-3 hours/week
[Database Systems](https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22ed2ee867-9610-4bad-94af-5d12c2ea47cd%22) | - | 27 hours
[Database Management Essentials](https://www.coursera.org/learn/database-management) | 7 weeks | 4-6 hours/week
[Intro to Artificial Intelligence](https://www.udacity.com/course/intro-to-artificial-intelligence--cs271)| 16 weeks | 6-10 hours/week
[Intro to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120)| 10 weeks | 6-10 hours/week
[Machine Learning for Data Science and Analytics](https://www.edx.org/course/machine-learning-data-science-analytics-columbiax-ds102x-0)| 5 weeks | 7-10 hours/week
[Big Data for Smart Cities](https://www.edx.org/course/big-data-smart-cities-ieeex-introdatax)| 4 weeks | 3-5 hours/week
[Processing Big Data with Azure HDInsight](https://www.edx.org/course/processing-big-data-azure-hdinsight-microsoft-dat202-1x-0)| 5 weeks | 3-4 hours/week
[Big Data Science with the BD2K-LINCS Data Coordination and Integration Center](https://www.coursera.org/course/bd2klincs)| 7 weeks | 4-5 hours/week
[Mining Massive Datasets](https://www.coursera.org/course/mmds)| 7 weeks | 8-10 hours/week
[Text Retrieval and Search Engines](https://www.coursera.org/learn/text-retrieval)| - | -
[Text Mining and Analytics](https://www.coursera.org/learn/text-mining)| - | -
[Cluster Analysis in Data Mining](https://www.coursera.org/learn/cluster-analysis)| - | -