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README.md

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 ### Single Variable Calculus
 [Calculus 1A: Differentiation](https://www.edx.org/course/calculus-1a-differentiation-mitx-18-01-1x)
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 [Calculus 1B: Integration](https://www.edx.org/course/calculus-1b-integration-mitx-18-01-2x)
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 [Calculus 1C: Coordinate Systems & Infinite Series](https://www.edx.org/course/calculus-1c-coordinate-systems-infinite-mitx-18-01-3x)
 
 ### Linear Algebra
 [Essence of Linear Algebra](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
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 [Linear Algebra](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/)
 
 ### Multivariable Calculus
@@ -57,35 +60,50 @@ OSSU Data Science uses the report [Curriculum Guidelines for Undergraduate Progr
 ### Introduction to Computer Science
 Students who already know basic programming in any language can skip this course
 [Python for Everybody](https://www.py4e.com/) 
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 [Introduction to Computer Science and Programming Using Python](https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-7)
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 [Introduction to Computational Thinking and Data Science](https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-3)
 
 ### Data Structures and Algorithms
 [Algorithms, Part I](https://www.coursera.org/learn/algorithms-part1)
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 [Algorithms, Part II](https://www.coursera.org/learn/algorithms-part2)
 
 ### Databases
 [Database Management Essentials](https://www.coursera.org/learn/database-management)
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 [Data Warehouse Concepts, Design, and Data Integration](https://www.coursera.org/learn/dwdesign)
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 [Relational Database Support for Data Warehouses](https://www.coursera.org/learn/dwrelational)
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 [Business Intelligence Concepts, Tools, and Applications](https://www.coursera.org/learn/business-intelligence-tools)
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 [Design and Build a Data Warehouse for Business Intelligence Implementation](https://www.coursera.org/learn/data-warehouse-bi-building)
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 [MongoDB for Developers Learning Path](https://university.mongodb.com/learning_paths/developer)
 
 ### Statistics & Probability
 [Introduction to Probability](https://projects.iq.harvard.edu/stat110/home)
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 [Intro to Descriptive Statistics](https://www.udacity.com/course/intro-to-descriptive-statistics--ud827)
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 [Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)
 
 ### Data Science Tools & Methods
 [Tools for Data Science](https://www.coursera.org/learn/open-source-tools-for-data-science)
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 [Data Science Methodology](https://www.coursera.org/learn/data-science-methodology)
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 [Data Science: Wrangling](https://www.edx.org/course/data-science-wrangling)
 
 ### Machine Learning/Data Mining
 [Machine Learning](https://www.coursera.org/learn/machine-learning)
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 [Intro to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120)
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 [Mining Massive Datasets](https://www.edx.org/course/mining-massive-datasets)
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 [Process Mining](https://www.coursera.org/learn/process-mining)
 
 ## How to use this guide