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74 lines
5.3 KiB
Markdown
74 lines
5.3 KiB
Markdown
# Computer Science - Great Courses
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This is a list of high-quality courses that, for one reason or another, didn't make it into the curriculum.
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The most common reasons are that the course isn't available often enough,
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or that there was an alternative that fit better into the curriculum.
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## Programming
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Courses | Duration | Effort
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[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
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[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
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[Introduction to Computer Science (Udacity)](https://www.udacity.com/course/intro-to-computer-science--cs101)| 7 weeks | 10-20 hours/week
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[An Introduction to Interactive Programming in Python (Part 1)](https://www.coursera.org/learn/interactive-python-1)| 5 weeks | -
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[An Introduction to Interactive Programming in Python (Part 2)](https://www.coursera.org/learn/interactive-python-2)| - | -
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[Programming Basics](https://www.edx.org/course/programming-basics-iitbombayx-cs101-1x)| 9 weeks | 8 hours/week
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[Object-Oriented Programming](https://www.edx.org/course/object-oriented-programming-iitbombayx-cs101-2x)| 4 weeks | 8 hours/week
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[Introduction to Programming with MATLAB](https://www.coursera.org/learn/matlab)| - | -
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[Introduction to Functional Programming](https://www.edx.org/course/introduction-functional-programming-delftx-fp101x-0)| 7 weeks | 4-6 hours/week
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[The Structure and Interpretation of Computer Programs](http://cs61a.org/) | - | -
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## Math
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Courses | Duration | Effort
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[Effective Thinking Through Mathematics](https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01x-0) | 4 weeks | 2 hours/week | none
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[Introduction to Probability and Data](https://www.coursera.org/learn/probability-intro)| - | -
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[Linear Algebra (Strang)](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/index.htm) | - | -
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## Systems
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Courses | Duration | Effort
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[Computer Architecture](https://www.coursera.org/learn/comparch) | - | 5-8 hours/week
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[Operating System Engineering](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-828-operating-system-engineering-fall-2012/) | - | -
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[Introduction to Operating Systems](https://www.udacity.com/course/introduction-to-operating-systems--ud923)| 8 weeks | 5-8 hours/week
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[Advanced Operating Systems](https://www.udacity.com/course/advanced-operating-systems--ud189)| 5 weeks | 5-8 hours/week
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[Computer Networking](https://www.udacity.com/course/computer-networking--ud436) | 12 weeks | 5-8 hours/week
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## Theory
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Courses | Duration | Effort
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[Algorithms, Part I](https://www.coursera.org/learn/algorithms-part1) | 6 weeks | 6-12 hours/week | some programming
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[Algorithms, Part II](https://www.coursera.org/learn/algorithms-part2) | 6 weeks | 6-12 hours/week | Algorithms, Part I
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[Analysis of Algorithms (Sedgewick)](https://www.coursera.org/learn/analysis-of-algorithms) | 6 weeks | 6-8 hours/week
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[Analysis of Algorithms (Skiena)](http://www3.cs.stonybrook.edu/~skiena/373/) | 15 weeks | 6-8 hours/week
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[Programming Challenges (Skiena)](http://www3.cs.stonybrook.edu/~skiena/392/) | 14 weeks | 6-8 hours/week
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[Data Structures and Algorithms (Specialization)](https://www.coursera.org/specializations/data-structures-algorithms) | 25 weeks | 3-10 hours/week
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[Algorithmic Thinking (Part 1)](https://www.coursera.org/learn/algorithmic-thinking-1/) | - | -
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[Algorithmic Thinking (Part 2)](https://www.coursera.org/learn/algorithmic-thinking-2/) | - | -
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[Statistical Mechanics: Algorithms and Computations](https://www.coursera.org/learn/statistical-mechanics/) | - | -
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[Approximation Algorithms Part I](https://www.coursera.org/learn/approximation-algorithms-part-1/) | - | -
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[Approximation Algorithms Part II](https://www.coursera.org/learn/approximation-algorithms-part-2/) | - | -
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## Applications
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Courses | Duration | Effort
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[Using Databases with Python](https://www.coursera.org/learn/python-databases) | 5 weeks | 2-3 hours/week
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[Database Systems](https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22ed2ee867-9610-4bad-94af-5d12c2ea47cd%22) | - | 27 hours
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[Database Management Essentials](https://www.coursera.org/learn/database-management) | 7 weeks | 4-6 hours/week
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[Intro to Artificial Intelligence](https://www.udacity.com/course/intro-to-artificial-intelligence--cs271)| 16 weeks | 6-10 hours/week
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[Intro to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120)| 10 weeks | 6-10 hours/week
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[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
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[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
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[Big Data Science with the BD2K-LINCS Data Coordination and Integration Center](https://www.coursera.org/course/bd2klincs)| 7 weeks | 4-5 hours/week
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# Online Learning - Great Courses
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Courses | Duration | Effort
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[Learning How to Learn](https://www.coursera.org/learn/learning-how-to-learn) | 4 weeks | 2 hours/week
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[Mindshift](https://www.coursera.org/learn/mindshift) | 4 weeks | 2 hours/week |