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Python

Python is an open-source programming language. The current version is Python 3. It is quite beginner-friendly, but also very versatile and powerful, making it suitable for many scientific appliances. As it contains packages for mathematics, scientific computing, statistics and plotting, it is a good all-around choice to use for data analysis. It also allows for more sophisticated methods such as neural networks and machine learning. Whatever your goal may be, be it to just be able to set up a basic reproducible analysis pipeline, or if you are willing to dive deep into the world of programming, Python is a good place to start.

Learning Python

But how to learn Python? There are a lot of options, and it depends on your goals and what works best for you what you should opt for.

  • A tutorial for Python in scientific contexts are the Scipy lecture notes. The best thing about it: There are a lot of exercises. Exercises are great—they are the best way to actually learn programming! Also it gets updated regularly, so that what you learn is up to date. Go for this option if you want to dive deep into the world of scientific computing with Python.

  • The Nipype tutorial contains a short introduction to Python that covers everything to use Nipype. Go for this option if you just want to learn the basics in order to be able to use Nipype.

  • Tutorial on data visualization in Python. Gives some additional options on how to make graphs.

  • If you have no experience in programming whatsoever, you might want to consider the book Learn Python 3 the Hard Way. The author follows the philosophy that in order to learn a programming language, you have to type everything yourself. It contains a lot of exercises and video material. Working through this book will give you a strong foundation to build further programming skills on. Downside: You will have to buy the book.