#Data Science Courses
##Prequiste courses
- A lite introduction to Python: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-189-a-gentle-introduction-to-programming-using-python-january-iap-2011/
- Intro to computer science (taught in Python): https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-00sc-introduction-to-computer-science-and-programming-spring-2011/
- Intro to algorithms: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/
##Free Books to Support introductory courses
- How to Think Like a Computer Scientist: http://www.openbookproject.net/thinkcs/python/english2e/index.html
- Learn Python the Hard way: https://learnpythonthehardway.org/book/
##Introductory courses
- Intro to machine learning: https://www.udacity.com/course/intro-to-machine-learning--ud120
- Andrew Ng's course: https://www.coursera.org/learn/machine-learning
- MIT's intro to machine learning: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/
- Intro to https://www.udacity.com/course/programming-foundations-with-python--ud036
##Intermediary courses:
- MIT's ml algorithmic course: https://ocw.mit.edu/courses/mathematics/18-409-algorithmic-aspects-of-machine-learning-spring-2015/
- UW's course notes: https://courses.cs.washington.edu/courses/cse446/16sp/ && https://courses.cs.washington.edu/courses/cse446/13sp/
##Advanced courses:
- Introduction to Neural networks: https://www.cs.toronto.edu/~rgrosse/csc321/
- Neural networks by Geoffrey Hinton: http://www.cs.toronto.edu/~hinton/nntut.html ##Books around the internet
- http://pythonbooks.revolunet.com/