If you want to do something that can take your Python coding ability to a different level, we suggest you go and take a challenge on Kaggle. Kaggle (www.kaggle.com) is a platform for predictive modeling and analytics competitions, which applies the idea of competitive programming (participants try to program according to the provided specifications) in data science by proposing challenging data problems to participants and asking them to provide possible solutions that are evaluated on a test set. The results of the test set are partly public, partly private.

The most interesting part for a Python learner is the opportunity to take part in a real problem with no obvious solution, which requires you to code something to propose possible solutions to the problem, even something simple or naive (which we suggest you start with first before getting involved in complex solutions). By doing so, the learner will come across interesting tutorials, beat-the-benchmark codes, helpful communities of data scientists, and some very smart solutions proposed by other data scientists or Kaggle itself in its blog, no free hunch (blog.kaggle.com).

You may wonder how to find the right challenge for yourself. Just have a look at the past and present competitions at www.kaggle.com/competitions and look for every competition that has knowledge as a reward. You will be surprised to find an ideal stage to learn about how other data scientists code in Python, and you can immediately apply what you learn from this book.