What is Python?

Python is a high-level, industry-leading programming language used to build websites (server-side), automate tasks, test software, and run data analysis. 

Python is an interpreted programming language that allows instructions to be executed without first being compiled into a machine language program. 

It’s also an object-oriented scripting language widely used in computer science. Further, Python enables artificial intelligence, machine learning, game development, system scripting, data visualization, and cryptography. 

Python is free and open-source software. This means that anyone can download it and use it for free. The main reason why Python is so widespread is that it is simple to learn and use.

How To Use Python

Python has become the most widely-used programming language for both rudimentary and advanced web development. It’s a great choice because it allows you to build scalable and maintainable applications quickly while also being easy to use for developers and non-developers alike.

Python is a powerful tool commonly used in the field of data science, where data analysts have utilized the language to create sophisticated statistical estimations. 

Data science is all about extracting useful information from large amounts of data. To do so, one must have a strong understanding of statistics, mathematics, algorithms, and other related fields.

However, many people are intimidated by these subjects and find them challenging to understand. Python is a perfect solution for data scientists who want to make sense of their data without worrying too much about the mathematical side.

You can quickly implement any algorithm or statistical technique using Python, as it’s also an excellent tool for machine learning. Machine learning is a field that involves building systems that can learn on their own. You can train these systems to perform specific tasks using prolonged learning capabilities.

For example, systems can learn to identify spam emails or recognize objects in images, though achieving this goal sometimes requires lots of training data. Python utilizes several open-source libraries such as Keras and TensorFlow, giving developers modern tools to write machine learning programs more efficiently.  

History Of Python

Python was developed by Guido van Rossum and the Python Software Foundation at the Netherlands-based research center Centrum Wiskunde & Informatica (CWI) in 1989. Python was officially launched in 1991 and has been re-released several times over the years. Eventually, it was released in its stable form in 2022.

The name comes from Monty Python’s Flying Circus, where van Rossum was reading the scripts from the BBC show when he thought of the name. Rossum thought the name Python was suitably snappy and intriguingly mysterious.

Python Examples

The python programming language has been around for some time and is one of the most popular languages used today. There are many different ways to use Python, from web development to data analysis and everyday tasks. Here are some examples of how you can use Python in your daily life.

It provides an interactive environment with powerful features such as object orientation, dynamic typing, integrated modules, automatic memory management, etc. Developers often use Python to create applications that need to be efficient at handling large amounts of data or performing complex calculations.

Python uses indentation to indicate blocks of code. This makes it easy to read and understand programs quickly. Python is also very flexible. You can write almost anything you want in Python, allowing you to solve problems differently depending on your requirements. Python is a multi-paradigm programming language. It supports multiple paradigms: imperative, fictional, structured, and reflective. Examples of Python use-cases also include syntax, variables, numbers, casting, lists, operators, etc.

Python Types 

Python has three main data structures: lists, dictionaries and sets. Lists are ordered collections of items. Dictionaries are unordered collections of key/value pairs. Sets are unordered collections of unique elements.


A list is an ordered collection of values that can be accessed using indices. It is similar to arrays in other languages such as C or Java. You can add new values to a list by appending them to the end of the list. To remove all the values in a list, simply set the length property to zero.


A dictionary is an unordered collection of key/value pairs that can be accessed using keys. You can access any value in Python using either a key or an index. If you do not specify a key, the default key will be used. You can assign a value to a key using the operator. To delete a key, simply set the corresponding value to None.


A set is an unordered collection that contains unique values. A set does not allow duplicate values. Unlike a list, which stores items sequentially, a set stores items randomly. When adding items to a set, you must check if the item already exists before storing it. Using the equality operator, you can determine whether two objects contain the same element.

Python Benefits & Drawbacks 

Python is a great language for beginners who want to learn to program. However, it is also easy to write bad code, which makes it challenging to maintain. If you’re looking for a language with many libraries available, then Python might be a good choice.

Python has been around for decades and is still one of the most popular programming languages used today. The main benefits of using Python include: it is easy to learn, it is free, and it is open source. However, some drawbacks to using Python: it’s sometimes slow, lacks documentation and doesn’t support object-oriented programming.

Continue Your Higher Education With TDI

There’s never been a better time to start learning new skills. Emerging technologies are revolutionizing the way we work, play, and live. Innovations in data science and machine learning allow us to explore beyond the deepest depths of the human mind to create something new and invigorating. 

Learning these disciplines deepens your understanding of the world around you and provides a fountain of knowledge to explore new frontiers and technological breakthroughs.

The Data Incubator offers an intensive training bootcamp that provides the tools you need to succeed as a data scientist. You will gain hands-on experience working on real projects and apply what you’ve learned in our curriculum to solve problems in your work or for clients. Our curriculum includes machine learning, natural language processing, predictive analytics, data visualization, and more.

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We’re always here to guide you through your data journey! Contact our admissions team if you have any questions about the application process.


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