AI News, The Guide to Learning Python for Data Science

The Guide to Learning Python for Data Science

Guest blog post by Martijn Theuwissen, co-founder at DataCamp.Other Python resources can be found here.  Python is widely used for data analysis and you might have considered learning it yourself (if not, or if you’re still looking for that bit of extra motivation to get started, see why you should be learning Python below).

We will discuss steps you should take for learning Python accompanied with some essential resources, such as the free Python for Data Analysis courses and tutorials from DataCamp as well as reading and learning materials.

There are good reasons why Python is being adopted so widely by computer scientists, and why it’s a data analysis tool of choice for so many, the main one being the ease of learning and using Python.

This free course consist of video tutorials and interactive in browser exercises and is a great way to learn by doing, as opposed to simply reading concepts and looking at examples.

While this course is not about data, but rather programming with Python, it is a great way to both practice with Python syntax and gain exposure to programming concepts that will be useful to you when working with data.

(Loading Data) The best way to learn and get comfortable with Python, or any other new programming language, is to take a sample dataset to work with, experiment, and try the new skills and techniques you pick up along the way.

To do so you can follow a sample code from available examples or forums like Stack overflow.  Always have your dataset available and treat it as a toy that you can play with and learn from.

The analytics begins with statistical modeling, machine learning algorithms, data mining techniques, inferences and so on.

Of course, as Python is a general purpose programming language, you are also free to program your own methods when you become an advanced user, though make sure you are not replicating what already exists.

Step 9: Mastering Python After learning the basics of Python and exploring the main tools and libraries with your sample dataset, you should proceed to taking some courses either for Python, or courses taught with Python to begin mastering the language.

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