Learn Python Online: Things that non-programmers must know

best data analytics courses in India

Last updated on January 23rd, 2024 at 07:26 am

Learn Python Online: Things that non-programmers must know

The developer of Python, Guido V Rossum, created it as a hobby project back in 1989. Today, Python has become one of the few official programming languages of Google due to its ease of use paired with efficiency. Python won the position of most popular programming language in 2020, as put forward by a joint survey of Google Trends and GitHub. In terms of programming language usage by global developers, Python has secured the third position in 2021, following JavaScript and HTML/CSS. Are you a non-programmer? Then Python can be your ideal starting point. And, here are a few things that you should know about this programming language.

Python: What is it?

It is an object-oriented, high-level programming language. It is a general-purpose, interactive programming language, the name of which is based on Rossum’s favorite TV series, “Monty Python’s Flying Circus.” The language is known for its versatility and simplicity, making it ideal for beginners and non-programmers.

What are the features of Python? 

Do you want to learn Python? Here are a few features to know about.

It can be integrated: 

Python can be integrated with an array of programming languages like C, C++, and Java.

Python is interpreted, and interactive:

Python can be processed by interpreters while they run it and a learner does not need to compile the program before execution. It is interactive because you can interact with the interpreter directly.

It is object-oriented:

Python is an object-oriented programming language and has code reusability. Designing an application with Python is easier with minimal coding.

Ideal beginner’s language

Python is characterized by the simplicity of structure, clear-cut syntaxes, and less number of keywords, thus making it simple to learn for any non-programmer. Furthermore, it is an open-source software freely accessible to all.

Why learn Python?

Tons of career opportunities:

The popularity of Python has contributed to the rising demand for Python programmers. Certification in data analytics can promise you an array of career choices.

Active community:

Program learning is not a solo sport. A massive community for providing the required learning support is vital to proper learning. Python has a considerable community backup which helps non-programmers in their learning.

Highly versatile:

It is a highly adaptable programming language that is used in multiple fields like web development, data science, software designing, and gaming. Python’s versatility is further enhanced by its ability to sync with a variety of other programming languages. Thus, it is a ‘cross-platform’ language.

Which fields use Python?

Python’s simplicity and ease of use have granted it access to a variety of fields like:

  • Web applications
  • 3D CAD-based applications
  • Software development
  • Auditory applications
  • Machine learning
  • Visual applications
  • Artificial intelligence

 Tips to keep in mind

Now that you know what Python is and what its features are, here are a few tips to keep in mind before opting for certification in data analytics:

  • Being consistent in code-making always helps to learn better. Are you making mistakes in coding? They are the stepping stones to your proper learning. So, code every day!
  • An interactive Python shell can be your ideal learning tool.
  • Opt for the pair programming technique, where you will pair with another developer. This way, you both will switch between writing codes and reviewing and problem-solving. Now, you can learn both sides of Python.
  • Opt for data analytics certification courses online, which can offer you the best possible resource to learn Python faster.

Conclusion

Are you looking for data analytics certification courses online? If yes, then you must check out the one offered by Imarticus Learning. With a fully online learning mode, this course is ideal for future data science experts and is backed by case studies, real-life business projects, and mentorship sessions.

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