Syntax, style, spaces, spelling #2 (#156)

* Syntax, style, spaces, spelling

* Syntax, style, spaces, spelling

* Syntax, style, spaces, spelling

* Update README.md

* Update README.md

CONTRIBUTING.md

@@ -1,4 +1,5 @@
-## Contribution Guidelines
+# Contribution Guidelines
+
 - Recently quality of MOOCs has diminished, therefore only MOOCs with comprehensive lecture material which cover a subject/topic in ample detail will be added. For example, MOOC on Computer Networks or Machine Learning with 4-5 hours may not be able to cover all topics in sufficient detail and thus should be avoided.
 - One philosophy used in this list while integrating MOOCs is that link should directly point to videos for viewing/downloading than registration and waiting for the next session. If videos are directly accessible through the platform/youtube or any other source, please use the direct source. This is list of video courses, not a list of MOOCs.
-- Courses within a section are roughly sorted in terms of level i.e. undergraduate courses followed by upper level undergraduate, followed by graduate courses. As courses are from multiple Universities, sorting is not perfect and only an approximation. For example, while adding a new undergraduate course on Algorithms, please feel free to add it along with other Algorithms courses than after graduate courses.
+- Courses within a section are roughly sorted in terms of level i.e. undergraduate courses followed by upper level undergraduate, followed by graduate courses. As courses are from multiple Universities, sorting is not perfect and only an approximation. For example, while adding a new undergraduate course on Algorithms, please feel free to add it along with other Algorithms courses than after graduate courses.

NOTES.md

@@ -1,9 +1,10 @@
-## Notes
+# Notes
+
 - Intent of this list is to act as Online bookmarks/lookup table for freely available online video courses. Focus would be to keep the list concise so that it is easy to browse. It would be easier to skim through 15 page list, find the course and start learning than having to read 60 pages of text. If you are student or from non-CS background, please try few courses to decide for yourself as to which course suits your learning curve best.
-- 90% courses on Data Structures/Algorithms/Operating Systems/Machine Learning/Computer Networks/etc tend to have 80-90% overlap in curriculum. Descriptions for courses are helpful but adding descriptions/comments for each course can lead to repetition/subjective opinions. As a tradeoff, metadata like course number, name, prof, year, University/platform for Course is added in the URL itself. To access syllabus/notes/assignments, please visit link to the course or use Google search with course number/name. If a course has excellent notes/assignments/projects which cannot be reached through video's link, please feel free to add links alongside. 
+- 90% courses on Data Structures/Algorithms/Operating Systems/Machine Learning/Computer Networks/etc tend to have 80-90% overlap in curriculum. Descriptions for courses are helpful but adding descriptions/comments for each course can lead to repetition/subjective opinions. As a tradeoff, metadata like course number, name, prof, year, University/platform for Course is added in the URL itself. To access syllabus/notes/assignments, please visit link to the course or use Google search with course number/name. If a course has excellent notes/assignments/projects which cannot be reached through video's link, please feel free to add links alongside.
-- If available, please add following information to the link - <Course-Number> <Course-Name> <Year> <Prof Name> <University Name/Platform>. 
+- If available, please add following information to the link - <Course-Number> <Course-Name> <Year> <Prof Name> <University Name/Platform>.
 - If you are bored reading above 10 lines, imagine reading descriptions for hundreds of courses :)
-- If You need assistance in deciding order in which courses should be taken, please refer to sample Course prerequsite charts by Universities to familiarize yourself with standard CS curriculum. If you need to know prerequisites for a particular course not covered by below samples, please check the course link or try Google.
+- If You need assistance in deciding order in which courses should be taken, please refer to sample Course prerequisite charts by Universities to familiarize yourself with standard CS curriculum. If you need to know prerequisites for a particular course not covered by below samples, please check the course link or try Google.
   - [MIT Curriculum Guide](https://ocw.mit.edu/courses/mit-curriculum-guide/)
   - [MIT New (Fall 2016) Degree Requirements](https://www.eecs.mit.edu/curriculum2016)
   - [Stanford Current CS Program Sheets](http://csmajor.stanford.edu/ProgramSheets.shtml)