Interested in learning Python? You’ve come to the right place! This comprehensive tutorial will get you up to speed quickly with the basics of Python.
Here’s what we’ll cover:
Released in 1991 by Dutch programmer Guido van Rossum, Python is a general-purpose programming language skyrocketing in popularity among data scientists. The Python language contains over 137,000 libraries, or pieces of reusable code, that simplify operations and experimentation. Its hallmark qualities are the simplicity and readability of the code and the wide array of tools available for big data processing and large-scale code.
One of the first technical languages taught in university settings, Python is relatively straightforward to learn and mirrors the human language in structure.
You can definitely learn Python programs on your own, and you don’t need prior experience or a degree to get started. Springboard offers a free Intro to Python for Data Science course and you can also explore other Python tutorials, lessons, and resources.
Here are some tips for learning the Python programming language:
Definitely not! Almost 45% of data scientists use Python as their preferred language, making it the most popular language today. It is the language of choice of Google, NASA, and CERN, among other large corporations. Facebook moved to Python and the pandas library because it was the same language used by the engineering team and easier to keep everything in a similar codebase.
Python supports back-end application and web development and complex mathematical computations. On the data science side, Python helps with data scraping and processing at scale, data visualization through packages like Matplotlib, and machine learning and deep learning.
Today, Python serves many purposes across diverse industries. It has predicted terminal illness progression for major medical centers, identified cross-sell opportunities for multinational financial services firms based on behavioral data, and enabled the aerospace industry to meet software system deadlines through time-efficient data mining.
Python also comes with machine learning specific libraries, like TensorFlow and scikit-learn, for those interested in exploring advanced topics around unstructured data and artificial intelligence.
Since Python is an object-oriented programming language, it can be easier to learn if you are familiar with a similar language like C++ or Java.
Python uses English keywords and user-friendly data structures, making it more readable and intuitive than R. For beginners, there are also easy-to-follow style guidelines, like PEP 8, and extensive support libraries.
Here are some tips for becoming a Python pro in no time:
With Python as part of your toolkit, you’ll be ready to attack almost any data science problem that comes your way with intellectual rigor and analytical depth.
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