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Viewing a YouTube tutorial on Python or browsing through the official documentation isn’t necessarily be the best way to learn Python. Without a reliable mentor in the programming community, it becomes incredibly difficult to quickly and efficiently learn new languages, primarily because students don’t know what they don’t know.
The hours spent searching for the content students need, taught well by the right teacher in the right context, would be better spent actually learning the language and preparing to apply it in the real world. And some ways of learning Python (or any language, for that matter) are much better than others. Read on to find out more.
Why Learn Python?
More than ever, today’s world is driven by software. Programming will remain an essential skill to learn in the future, regardless of chosen industry. Of all the programming languages in circulation today, Python stands out as one of the most versatile and easy to use, as we explain below.
Python is Beginner-Friendly
The Python programming language is readable and its syntax forgiving, making it friendly to developers of all skill levels. Its cross-platform nature means it can run on any machine. Furthermore, Python is built with modern design paradigms like object-oriented programming in mind. Its compatibility with software architectural best practices means beginners will save time and effort starting off with a language ready for modern development. By building these design constructs into the language, using Python avoids training bad habits and practices early in your development career and onward.
Python Has a Strong Ecosystem
In addition to the benefits of the language’s design, Python has a massive ecosystem. Its vast community has created packages and open-source libraries for nearly every imaginable use case. No matter the project you’re working on, chances are that at least some parts of that project already exist in Python’s ecosystem of libraries.
This ecosystem includes libraries that specialize in modern, active disciplines like automation, research and data science. Libraries such as NumPy, pandas and Matplotlib can provide vital assistance in a data scientist’s workflow. They can add powerful mathematical capabilities, data visualization tools and data preparation operations to Python, making data science research and development a breeze.
Python is a Popular Choice for AI
The same applies to the development of artificial intelligence, without a doubt a hot topic these days. Check out our article dedicated to Popular Python AI Libraries for more information. Python now provides native support for numerous applications from machine learning to expert systems and natural language processing, so AI developers need look no further than Python to find the resources they need for their projects.
Use Python for General Automation
Alongside Python’s tremendous research capabilities, it can also add value to commercial endeavors with its robust automation. You can automate almost anything using Python, from sending emails to creating invoices and scripts to automatically scraping data from websites (check out Automate the Boring Stuff with Python for more use cases). With most of the automation legwork completed for you in the form of libraries available in the Python ecosystem, a simple package installation is all it takes for automation to start making your business more profitable and easier to run.
All that’s left for you to do is to dive in and learn Python.
Best Ways to Learn Python
1. Contribute to Open-Source Projects
Learning by building projects is one of the best ways to absorb knowledge that can’t be explicitly taught. If you’re not ready to develop your own projects, open-source projects allow you to contribute to real-world applications without having to come up with the original concept yourself. Participation and a penchant for learning are all that’s required to learn Python this way.
There’s a multitude of resources that can help developers discover new open-source projects open to contributors. Sites like First Timers Only provide comprehensive, multi-step guides that help new developers find not only projects that accept contributions but also healthy projects to contribute to — for example, ones with published codes of conduct. Up For Grabs also offers a search engine for projects actively seeking new contributors.
Perhaps the most comprehensive solution for connecting developers with open-source projects is CodeTriage. The site works by picking a set of issues affecting some open-source projects, then notifying and assigning developers to them based on repositories they selected. It saves developers time hunting for projects and gives them the ability to effect meaningful change.
2. Go Through a Python Tutorial
For those still working up the confidence to get building straight away, taking a Python tutorial can provide the right learning environment to bootstrap your development skills. A guided tutorial saves you having to hunt for the right resources and content that can teach you what you need to know. The end result is a deeper and more durable comprehension of Python, as opposed to the shallow understanding that will inevitably result from quick Google searches and browsing Stack Overflow.
Typical curricula involve first learning the basics of Python and its syntax and then going over specific features of the language, for use cases in data science or web development. You can expect to learn about native Python data types (like lists and dictionaries) and some popular Python libraries applicable to your specific use case. All of this takes place in a controlled environment focused on absorbing concepts rather than the potentially overwhelming nature of a real-world project.
3. Earn the Full Stack Web Development Nanodegree
Clearly, the ideal solution to learning Python is a combination of learning in an academic environment and building projects. Combining learning and application in one setting is crucial for learning the ins and outs of Python as well as for getting yourself job-ready.
Udacity’s Full Stack Web Development Nanodegree does exactly this. Over the course of four months, students participate in real-world projects from top-tier companies and gain access to personal career coaching and mentorship services. Under the umbrella of web development, students use Python to model data, develop APIs, implement authorization and authentication and deploy web apps to servers.
Unlike doing Python tutorials and open-source projects separately, Udacity instructors and mentors direct students through practical projects, creating a link between academic practice and the real world. This is undoubtedly the best way to learn Python.
Learning a programming language is one of the best ways to boost your career prospects and get ready for the modern job market. Among all programming languages, it’s clear that Python ranks as one of the most friendly for new students. To learn Python, developers can delve into the world of open-source projects to learn by application or take one of the widely available Python tutorials that direct them step-by-step through the nuances of learning this programming language.
Udacity’s Full Stack Web Development Nanodegree offers the best of both worlds, combining real-world applications for developers to work on with an academic setting that provides students with the guidance they need to learn Python in the most efficient way. If you find yourself wanting to learn Python without needing to search for the best tutorials or the most developer-friendly open-source projects, sign up for Udacity’s Full Stack Web Development Nanodegree.