Wed. Mar 3rd, 2021

If you want To automate some tasks on your desktop or to explore a new career in technology, learning Python can help you do so.

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It is known in developer circles as a programming language that can meet a wide variety of needs, and is easier to choose than some alternatives. Perhaps that’s why Python is so popular. according to PYPL Index, Which tracks how often programming language tutorials are searched on Google, Python ranked No. 1 worldwide by June 2020.

Here to find out if Python is worth learning and what classes or other resources can help you get started

Python was created in 1991 by programmer Guido van Rosum, who nominated it for the British comedy series “Monty Python Flying Circus”. It could be used easily, but was also powerful enough for many jobs. You can use it to build a simple calculator, develop a website, or even employ machine learning techniques as a data scientist.

“Python as a language is very adept and enables a wide spectrum for all skill levels,” says Sabin Thomas, vice president of application security engineering for Threat Stack Inc., a cloud security company.

A lot of factors make Python well suited for large and small tasks. The language is open source, which means that users can change and share it at will. Python users can take advantage of free suggestions and custom programs imposed by large communities of open-source enthusiasts and Python developers. Finally, Python comes with a robust standard library, which can help speed up troubleshooting or development efforts, minimizing the amount of original code users will have to write.

Another key feature of Python: it can perform the same basic tasks to other languages ​​using very simple code. Its syntax refers to rules that describe how programmers can use code, part of the reason why.

Most programming languages ​​have complex rules, and the code is often defined by a group of characters that may look like gobbledygook to people with no programming background. The syntax of Python is so simple that when you start you will find yourself using mostly natural language words.

For example, if you want to display “Hello, and Welcome to Python” on the screen, just type:

print("Hello, and Welcome to Python")

For Java – not coffee but the programming language – to display “Hello, and Welcome to Python” on the screen, users must type:

public class HelloWorld {
    public static void main(String[] args) {
        System.out.println("Hello, and Welcome to Python");
    }
}

An easy syntax also makes it easy to use other elements in Python. It consists of functions, lines of code represented by characters, which run when called. Users can input a series of requests into a function, and it can return an output in the form of data or manipulate other parts of the program.

In Python, you can define a function using the default keyword command. for example:

def my_function():
    print("This is a function.")

Calling the function my_function () runs the code defined within it, without rewriting all of it. In the above example, calling that function will display the text “This is a function”.

Programmers at Python start a series of statements several times. An example is the “for” loop, which visits each item in a sequence.

cars = ["Corvette", "Ferrari", "Lambo", "Ford"]
for y in cars:
    print(y)

In Python, it displays each item described in the command (y), and the programmer gets this output:

As loop statements seem simple, when you have to go through a large list because you do something like build a big website, these simple statements can be amazingly useful. They are also helpful when shifting to more complex uses for Python, such as data science and machine learning.

Data scientists use programming languages ​​such as Python to gather data and generate insights that their organizations can perform. although Data science A separate field from computer science, data scientists often use concepts from computer science to help create programs and analyze data.

What makes Python well suited to data science are the same features that make it popular in other areas – its scalability, large community, and ease of use. In addition, Python is a flexible language, which allows data scientists to use it to solve many problems.

One tool in the data scientist’s tool belt is machine learning, which has the ability to create data to interpret a computer to predict an outcome. Python has several libraries that make it easy for machine scientists to use machine learning techniques. For example, the Skikit-Light library is a popular option for those who want to keep things like cluster data in a cluster or develop regression, which helps to show relationships in the data set.

Python Council calls the ability to value advanced machine-learning-based capabilities called neural networks and data science holistic, with Tate Nurkin, Atlantic Council think tank and CEO of consulting company OTH’s Forward Defense Initiative Says non-senior senior partner. Intelligence group. Both neural networks and data science, he says, “are central to the future of almost every industry, and certainly to the future of defense, security capabilities, and operations.”

Python is free to download and use. To begin, visit Python Software Foundation website And select your operating system – Python works on Windows, iOS or Linux. Then, follow the instructions.

Python 3 is the most current version. While some older code may use Python 2, according to the Python Software Foundation it is no longer supported. An important difference between the two is the syntax behind some statements. For example, Python 3 uses parentheses in the print function. Not Python 2.

After downloading Python, you will need some tools. Here are some of the most recommended:

  • Jupiter notebook May allow users to write code more easily and collaborate with others.
  • Python debugger, Which is available in Python’s standard library, helps users find and fix code errors.
  • Ipython Functional is the user interface preferred by some programmers to support data visualization capabilities.

You also want to use some major libraries. In his blog, Software Development Company Django Stars Python recommends these libraries for programmers interested in data analytics and machine learning:

YouTube has a wealth of videos on Python tips and tricks. Check it out Cs dojo channel To know the basics. If you are new to technology, consider taking introductory classes offered from online institutions such as Dataquest, LinkedIn Learning, Coursera or edX.

When you are starting, set some goals. Consider focusing on the most common orders and the most popular means in the first two months. During months three and four, reinforce basic programming knowledge with a short project. During this phase, it is important to be familiar with online forums stack Overflow And Codecademy To create a community of cooperation and feedback for difficult issues arising later in your development.

If you have experience programming in other languages, learning Python to make a career in Python programming can be very short for a couple months.

Programming hero, Which offers interactive coding tutorials, says that you can learn Python in two months. But it is believed that you can sit in front of a computer every day and practice from 8 am to 5 pm

If you have a day job, six months may be a more realistic timeline. To work on a computer learning Python, you must spend two to three hours a day, at least five days.

Keep in mind that the roles of a Python developer or programmer can be quite diverse. Not only that, but you can also use Python as a back-end web developer, data scientist, quality assurance engineer or system engineer. Each of these jobs requires different knowledge about using Python and common tooling to fulfill the role’s responsibilities.

As you learn Python, focus on how to apply the language to that role.

The time and effort required for a Python programming job depends on your experience. It is important to demonstrate your skills through relevant Python projects. You also want to create a website showing your projects and achievements.

according to this Execution, In an online boot camp, a portfolio shows prospective employers the ability to solve your problem and write your code and document your steps. (If programming was done like cooking, the code would be cake and your ability to write documentation recipe.)

It also shows that you can apply your coding skills to different situations and take advantage of online resources. Online learning site Simplilearn Suggests starting a repository Github, A website that can house your portfolio and resume. That way, you can share your work samples with recruiters, neatly packaged in zip files.

It is also important to be able to discuss other programming languages ​​that you like. Nobody wants a Python robot. Good programmers dub all kinds of code and tech. Be prepared to talk about what you found easy and difficult about learning Python, and the big challenges you have faced in the past, not only with code, but with technology in general, and you have completed them. The steps to be taken.

Many Python roles require applicants to have experience with agile, a growth mindset that emphasizes collaboration and the ability to switch gears as plans change.

“Proving that you can collaborate with others to solve problems is an important aspect during the job interview process,” Narkin said. “It’s one thing to be a solid programmer, it’s another thing if you’re a programmer who works well with others to solve big challenges.”

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