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 and online resources:
- Zelle, J. (2017) Python Programming: An Introduction to Computer Science, Third edition. Franklin, Beedle & Associates. Copies of this book are available in the Kumpula Campus library.
- McKinney, W. (2017) Python for Data Analysis: Data wrangling with Pandas, NumPy and iPython, Second edition. O´Reilly Media, Incorporated. Available as Ebook in here.
- Learn Python the Hard Way Free sample of the book is available on the webpage.
Python tutorials¶
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