As a data scientist, one of the first skills that you might have heard you should equip yourself with is the programming language of Python. If you hadn’t studied computer science stream in high school or college, you might be intimidated to learn a new programming language, especially when you aspire to start your career in data science. So, the first question that comes to your mind is, “Is Python compulsory to become a data scientist?”
We are here to answer this question for you. The short answer to this question would be yes. We wouldn’t as much use the word, “compulsory”, because “necessary” would be a better word for this question. Yes, Python is definitely necessary for a data scientist. However, the good news is that it is a very easy language to learn. So, even if you have no prior knowledge of computer science or programming language, you can learn the basics of Python in about two months easily.
Why is Python important for data science? How is it used in data science? Why is it one of the easiest programming languages to learn even for beginners? Keep reading to know the answers to these questions and more.
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Python – Basic Features
Python is said to be the base for all the work done in the fields of data science and data analytics. So, knowing the fundamental concepts at least is of paramount importance to aspiring data scientists and analysts. Before you proceed to learn this language, it is good to know some of the basic features of Python, which are listed below:
Open-Source Language
An open-source language is one that is freely available online to learn and develop. You can download the language and its codes freely and use them in the way you want. You can also make changes to the codes, and upload these changes freely online. This way, others can download these updated codes, when they face a similar situation. Python is heavily dependent on its community of online users who keep releasing updated versions of these programs. Since it’s an open-source language, it also allows users to access its unlimited libraries like TensorFlow, Keras and more,
Ease of learning
Though there are many programming languages in the world, Python and R are the most commonly used ones in data science today. Python, especially, is very popular because it is easy to learn. Its syntax is easy because it mimics simple English words. Even if you are a beginner, you will find Python easy to learn, because you don’t have to memorize any complex codes here. As long as you understand the reason behind why the codes are written, you can remember the codes easily.
Another interesting feature of Python is that it is a forgiving language. This means, the program can still work if it has a few errors in it. This makes it easy for beginners to grasp the concepts of the language and Python codes easily.
Flexible and versatile
Though we keep insisting that Python is an easy and simple language to learn. Python is versatile enough to be used for complex web development and writing scripts for various applications. The codes are flexible enough to be used on various devices. This way, you don’t have to write new codes every time you run it on a new device, saving you a lot of time and effort. Python is dynamic, too, because you can determine the type of the variable used here even in the middle of the runtime, unlike most other languages that require you to set up the variable type at the beginning itself.
Why is Python necessary for data science?
Python plays a very important role in data science because this language is used in many areas of this field. Some examples of where Python is used for data science are given below:
- Machine Learning
Machine Learning, deep learning, Artificial Intelligence and Natural Language Processing are some of the buzzwords in the data science industry today. Python, with its new trends, tools and modules, is one of the most used programming languages for designing machine learning algorithms that are used extensively throughout all industries today. Data scientists can access the vast list of Python’s libraries like TensorFlow, Keras, Numpy and Scikit Learn for working on AI and Machine Learning related projects.
- Gaming
With the gaming industry growing phenomenally in the last few years with games like Minecraft and Candy Crush Saga ruling the roost, it is not surprising to know that Python plays an important role in this too. Thanks to its easy web programming techniques, AI compatibility and other features, Python is a great language to develop all sorts of games, even 3D ones.
- Education
Today, many people opt for online training courses (free or paid versions) to hone their skills in a particular domain. Python is the most-used programming language to develop these training and certification modules. Think about this – when you want to develop your knowledge of the basics of Python, the courses that come up online are all designed using the very language you want to learn!
Python and Data Science are inseparable
Python is an object and procedure-oriented language that offers users access to unlimited libraries to quicken and fasten their programming tasks. Thanks to these libraries, you can handle large volumes of data with minimal errors in your day-to-day job as a data scientist. Some of the most frequently Python libraries in data science are NumPy (highly effective for data analysis due to its multifunctional tools), Matplotlib (great for presenting the final data in an effective visual format) and Pandas (used for practical projects involving extensive analysis, statistical and engineering skills).
Bottom Line
As you can see, knowing Python is a prerequisite for a data scientist. However, learning this programming language is not a daunting task, as the language is easy to grasp, even for beginners. Also, there is a huge, online Python community to help you with your queries and issues, if any. So, you can connect with them to widen your knowledge, after learning the basics of the course from a reputed institute like 360digiTMG Pune. This way, you can get thorough knowledge of Python quicker than you expected.
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