How Difficult is Python to Learn?

Python is considered one of the easiest programming languages you can learn. Its relative simplicity, however, does not detract from its power and utility as a language. Python, in fact, is one of the most popular programming languages used in large tech companies, training programs, universities, and small startups alike.

When it comes to learning programming, Python is the best language to start with due to its user-friendly nature. It has a more intuitive coding style and has many other advantages for Developers and end users. That’s part of why Python Programming Courses have become so popular; after a short certification course, you can be armed with one of the most-wanted skill sets on the job market.

Another reason Python is so easy to learn? It’s accessible. Python is available on its official website, free of cost. On top of that, being open source means that you or anyone else can update and add new features in Python.

Further, Python can run efficiently across all platforms like Windows, Mac, or Linux. Therefore, it is not dependent on or restricted to a single platform.

Professionally, Python is often used for backend web development, artificial intelligence, and data analysis. This programming language has already been used to build productivity tools, games, and desktop apps.

Is Python Hard to Learn for Beginners?

Python can be considered beginner-friendly, as it is a programming language that prioritizes readability, making it easier to understand and use. Its syntax has similarities with the English language, making it easy for novice programmers to leap into the world of development.

Python is also a flexible, dynamically typed language, which means the rules aren’t hard set, making it more intuitive. It’s also a more forgiving language that is able to operate with some level of errors.

In fact, ease of use was one of Python’s founding principles when it was created in 1989 by Guido van Rossum (and released later in 1991). The initial purpose of Python was to make programming easy, as it focused on code readability. It’s also flexible. It can run on diverse platforms such as Windows, Linux, and Mac OS, and is open-source software.

Because the readability and other structural elements of Python are designed to be easy to understand, it is a great language for beginners. However, Python is not limited to basic use. It supports some of the most complex websites and apps in the world.

Python has support for all of the features of an object-oriented programming language, as well as a procedural-oriented programming language. As a result, it’s not a coincidence that Python is the preferred choice for Developers, Data Scientists and Software Engineers.

Can I Learn Python on My Own?

Yes, with its relative simplicity, it is possible to start learning Python on your own. It’s very easy to install the language and run it from anywhere on your machine. If you run into problems, there is a large and very dynamic user-base for Python, making it easy to find a community that’s willing to answer questions.

To accelerate the learning process, a large number of aspiring Python Developers are enrolling in Python courses, like BrainStation’s Python Programming certificate course, to gain hands-on experience and learn from experienced industry experts. Coding bootcamps and Python courses have become an increasingly popular option, and not only for neophyte Python Developers – as in other tech fields, Python experts need to keep learning to stay on top of changes to languages, techniques, and trends.

Another great thing about Python is the wealth of documentation available at Python.org. There are also a plethora of websites that allow you to practice Python and stay up-to-date, like practicepython.org or codingbag.com. Contributing to an open-source commons, such as GitHub or Bootstrap, can also help you stay informed.

If you want to know whether a specific application, or a library with a specific functionality, is available in Python there are lots of sources of information. The Python web site provides a Python Package Index (also known as the Cheese Shop). There is also a search page for a number of sources of Python-related information.

How Long Will it Take to Learn Python?

On average, it can take anywhere from five to 10 weeks to learn the basics of Python programming, including object-oriented programming, basic Python syntax, data types, loops, variables, and functions. In the end, though, the length of time it can take to learn Python depends on how much experience you have with programming languages, web development, or related fields.

In a bootcamp Python course like BrainStation’s, you’ll learn core concepts like libraries, dictionaries, and lists, which are required knowledge for a data-focused role. The right training will give you a fundamental understanding of Python, which in turn enables you to learn more complex machine learning and data science concepts moving forward. Python, however, is relatively easy to learn. Though it’s dense, with a multitude of libraries to learn and cipher through, Python’s syntax is considerably simple, and its concepts are relatively straightforward. The easy syntax makes for quick learning and contributes to a generally intuitive and streamlined coding experience. That really eases the workload on your brain as you delve into bigger and more complex projects.

Python is also a very versatile language. It is used in many different types of projects and by many large organizations, including Facebook, NASA, Reddit and Amazon. Big companies love its power and versatility, so the language can be expected to continue to rise in popularity around the world. There’s hardly a tech job that you can’t apply Python to, which will make you more valuable to any employer or client.

Python’s robust array of libraries streamlines the coding process immensely since you can simply input an action from the library into your code. Even better, since Python is open source, the list of libraries and resources are constantly growing. As Python gains even more popularity, users will find more versatile libraries that will help them write more code in less time and streamline existing content.