Why Study Python in College? 12 Factors Contributing to the Current Heat Wave

Coding is arguably the most important skill for todays and future generations. Learners can solve problems creatively and logically by using various programming languages.

Most college students select a coding boot camp based on the programming language they wish to learn. Python has recently become the most popular language among college students in data science and coding boot camps. Here are the reasons why Python is so popular right now.

1) Python is extremely versatile, with numerous applications.
Python is used in Data Mining, Data Science, AI, Machine Learning, Web Development, Web Frameworks, Embedded Systems, Graphic Design applications, Gaming, Network development, Product development, Rapid Application Development, Testing, Automation Scripting, and so on.

Python is used as a simpler and more efficient alternative to languages such as C, R, and Java that perform similar functions. As a result, Python is becoming more popular as the primary language for many applications.

2) Python is easier to learn

Python is consistently cited for having a gentle learning curve that most college students find easier to adapt to. Unlike other programming languages like C++, Python has most of its libraries organized, which means that you won’t have to struggle a lot to create new libraries.

Python allows you to express a lot of functionality more clearly with a few lines of code than other programming languages. If you are assigned to write an essay on Python in college, you can easily relate to the various classes and functions used or seek assistance from the available essay sites that provide assistance 24/7 days.

Python has scalability.

3) Language Interpretation
Python is an interpreted language, which means that the code is executed line by line. In the event of an error, it suspends further execution and reports the error.

Even if the program contains multiple errors, Python displays only one. This facilitates debugging.

4) Python is Portable
Many programming languages, such as C/C++, require you to change your code in order to run the programme on different platforms. Python, on the other hand, is not the same. You only need to write it once and then run it anywhere.

You should, however, take care not to include any system-dependent features.

5) Python has Compatibility with the Internet of Things(IOT) devices
The Internet of Things (IoT) is a network of physical objects linked together by sensors, various software, and other technologies. In most cases, it works without requiring human-to-human or human-to-computer interaction. If you look around your neighborhood, you will notice that IoT devices are everywhere and taking on new forms as their levels of communication advance.

6) Provides Maximum Flexibility and Extensibility

Python gives you the flexibility, scalability, and extensibility you require. Because it is a cross-platform language, it works well on all platforms, including Windows, Linux, and macOS. You should also be aware that if you want to execute Python code written for Windows, Mac, or Linux – you can do so without difficulty. Python enables developers to easily perform cross-language operations and can be easily integrated with Java,.NET components, or C/C++ libraries.

Its extensive nature enables it to be effectively extended to other programming languages. Furthermore, because Python is an interpreted language, you do not need to compile your program before running it, as you would with Java or C++. Furthermore, it is a dynamically typed language, which means that you do not need to specify the data type when declaring it. Python is, in fact, a more flexible, portable, and extensible programming language when compared to other programming languages.

7) Open-Source and Free
Python is distributed under the OSI-approved open-source licence. As a result, it is free to use and distribute. You can download the source code, modify it, and even distribute your own Python version. This is beneficial for organizations that want to change a specific behavior and use their version for development.

8) Libraries and Frameworks:

Python has a wide range of open-source libraries, frameworks, and modules at your disposal to do whatever you want. When compared to other languages, it makes application development extremely simple.

It simplifies your job because you only have to concentrate on business logic. Python has a plethora of libraries and frameworks to meet a variety of needs. For web development frameworks, Django and Flask are two of the most popular, while NumPy and SciPy libraries are for data science.

9) Excellent, open community
Python has a large and illustrious community that has been at the forefront of data science and machine learning projects for decades. Robotic engineering is advancing rapidly in various parts of the world, including medicine and disaster management, thanks to Python.

When deciding on a programming language to study at the college level, consider the available learning resources as well as the impact of the wording on community projects. Human labor is included in learning resources because, in most cases, you will need to consult with your friends to fix bugs that you will encounter.

10) Website Design and Development
Learn Python to make your development process as simple as possible. There are numerous Django and Flask libraries and frameworks available to make your coding more productive and efficient.
When comparing PHP and Python, you’ll notice that the same task can be accomplished in PHP in a matter of hours. However, with Python, it will only take a few minutes. Take a look at the Reddit website — it was built with Python.

some full-stack Python frameworks for web development are:
Django, Pyramid, Web2py, TurboGears

here are some Python web development micro-frameworks:
Flask, Bottle, CherryPy, Hug

There is also an alternative framework you may want to consider:
Tornado

11)Python in machine learning and artificial intelligence

Python is used in machine learning and artificial intelligence, both of which are at the cutting edge of technology.
Machine learning and artificial intelligence are everywhere, from Uber ETAs to Google finishing your sentences and Netflix predicting which shows you’ll like.

It’s exciting to think about where we’re going when we consider how recent many of these developments are. Without a doubt, Python will be at the forefront of AI innovation.

Python, according to experts, is the best programming language for machine learning and artificial intelligence. Its extensive libraries and frameworks are ideal for getting new ideas off the ground (more on this later). Furthermore, it is relatively brief and supported by a large community of programmers who are known for documenting their successes and failures.

So, if you want to be in “the room where it happens,” the apex of the most exciting new technologies like machine learning and more, learning Python is unquestionably beneficial.

12)Python in Automation or Robotics
Using Python automation frameworks such as PYunit provides numerous benefits:
There are no additional modules to install. They come in a box.
Even if you have no prior experience with Python, you will find working with Unittest to be very easy. It is derived, and its operation is similar to that of other xUnit frameworks.
You can conduct isolated experiments in a more straightforward manner. You should simply type the names into the terminal. The output is also compact, making the structure adaptable when it comes to running test cases.
The test reports are produced in milliseconds.

Conclusion

Python is one of the high-level, object-oriented programming languages with built-in data structures and dynamic semantics that college students can easily learn. You will learn a variety of programming paradigms, such as structures, functional programming, and object-oriented programming, which are highly applicable in a variety of fields. Learning this programming language will also introduce you to other modules and packages that facilitate program modularity and code reuse.