Resources ========= In addition to our course, there are countless of excellent books, tutorials and examples related to programming in Python. Here we list some good places to look for further information. Books ----- There are **no required textbooks** for this course. This course uses a wide range of sources for course information and the main textbooks are given below. - Recommended textbooks (in order of relevance): - Zelle, J. (2010) `Python Programming: An Introduction to Computer Science `_, Second edition. Franklin, Beedle & Associates. - McKinney, W. (2012) `Python for Data Analysis: Data wrangling with Pandas, NumPy and iPython `_, First edition. O´Reilly Media. - `Learn Python the Hard Way `__ - `Dive into Python 3 `__ Python tutorials ---------------- - `Codecademy's Learn to program in Python `__ - `Software Carpentry's programming in Python `__ Git + Github tutorials ---------------------- - `Online "Try-Git" tutorial (learn Git in your browser) `__ - `Git simple guide ("no deep shit") tutorial `__ - `Software Carpentry's Git novice tutorial `__ - `Git official documentation `__ - `Screencast series in Youtube for learning GitHub `__ - `Tutorial on few extra features of GitHub not (most probably) covered in this course (e.g. branch, pull-request, merge) `__ - `A TechCrunch article about 'What is GitHub Anyway?' `__ - `A list of resources for learning Git and GitHub `__