There are many data science courses that teach you the skills, tools, techniques, and methods that help you become a successful data scientist. Data science is an extensive field that uses scientific methods, algorithms, processes, etc., to extract knowledge from structured data as well as unstructured data. This knowledge is further applied from data to a broad range of domains.
If you are aspiring to become a data scientist, it is best that you learn everything – ranging from tools to programming languages. To learn data science, one must have a good knowledge of Python and other programming languages. Python is one of the most used languages by every developer and data scientist.
But what is Python? Python is defined as a programming language that is used to build websites, user interfaces, software, etc. For conducting analysis as well, Python is used. Today, this programming language is used in a variety of sectors like business, web development, machine learning, etc.
Python is regarded as the top programming language which is easy to learn and understand. Every aspiring data scientist and data analyst must do a Python course or take up Python training to learn the basics of the language. Used by all sectors, this language has now become mandatory to learn. Whether you are a data scientist or not, learning Python is going to give you an edge over others!
Surprisingly, Python has surpassed Java and has become the top programming language. Many data science courses teach you Python along with the techniques and methods of data science. Candidates can apply to these courses and begin their journey as data scientists in top positions and high-paid jobs.
Now, there are several reasons to learn Python for Data Science. Here, we will explore these reasons. So, let us discuss them in detail!
Why Should You Learn Python for Data Science?
Data Science is an extensive field that includes several things. Python has become necessary to learn to become a data scientist. Python is one of the fastest, easiest, and most fun ways to make its way into the field of data science.
Data science is a valuable skill that provides people with high salaries and top job positions. Here are the reasons why one must learn Python for Data Science.
- Easy to Learn
We understand that coding can be a bit intimidating. But a programming language like Python is quite easy to learn. It has a remarkably easy syntax and vocabulary as compared to other programming languages like C++, Java, C, etc. Python is an obvious choice for people taking up data science. Python is a simple tool that can be learned without taking much effort.
- Readily Understood
Python has a simple syntax that includes easy English language. It can be understood by people who have no experience with Python. A beginner might think that coding will be difficult to learn. It is not so! Python can easily be read by people as coding in data science with Python is extremely easy. Python tends to make everything easy.
- Python is Popular
Python is one of the easily used languages in data science. It is the third-most widely used language. Many companies use Python for frameworks and projects. For example, Google, TensorFlow, Facebook, etc., use Python for their data science projects. If you aspire to get into the field of data science, then it is essential to know that you will not get far without learning Python. So, it is essential to learn Python for a better understanding of the processes and algorithms of data science.
- Data Libraries Set
One of the benefits of learning Python for data science is that one gets access to a comprehensive set of data libraries. There are several libraries such as Pandas, Statsmodel, SciPy, NumPy, etc. These libraries are immensely popular in data science communities. The ecosystems made by them help in completing the tasks at a faster rate without hampering the quality. Python libraries are constantly evolving to help data scientists and data analysts.
- A Great Way to Learn Fundamentals
Python has an unlimited number of applications, but there is a lot of overlap between data science and Python. One can easily learn Python by enrolling in some courses or watching some tutorials. Data scientists primarily use Python to retrieve, clean, visualize, and build models. This is the basic knowledge that is taught to the candidates in courses.
For instance, one can start by learning the ways of setting up the environment, importing data, cleaning it further, and running stat analysis on it. By taking up a data science course, a candidate will learn the basics of Python which will help him/ her, in the long run, to build various models and analyze them further.
- Big Community
One of the prime benefits of learning the Python language is that you will get access to an incredible community of people who love Python. There is a huge and enthusiastic community of people who share their insights, experiences, tips, etc., which they have gained in the journey of learning and working with Python.
We understand that one might feel pressured while learning programming languages. This is the reason communities are built. They make it easier to understand the language and give you some pro tips that not everybody gets!
- Data Cleaning
Data science also involves data cleaning and Python is great at doing this! Data cleaning removes almost 80% of the workload of data scientists. If you wish to become a data scientist, then it is important to come to terms with data scrubbing, massaging, cleaning, wrangling, etc. This is one of the characteristics of data science that makes Python a necessary topic of learning. Python is built to clean the data. Among the libraries, candidates can make use of NumPy and Pandas for cleaning! Thus, Python is really a smart choice.
After you have completed the process of data cleaning, the next vital component is communicating the findings. Data Science is not just about coding. It is also about communication with the stakeholders and consumers. A lot of people are of the view that data scientists only analyze things. That is not the case. Python has a lot of great tools to undertake data visualization. If a data scientist can easily illustrate the data and communicate effectively with the stakeholders, then half the battle is won! Python makes communication easy for data scientists.
- Rapid Prototypes
It is a rarely known fact that data science models and projects are quite expensive. To get things around in time and at cost, many data scientists use prototypes so that they undertake a dry run of their idea along with a stress test to make sure that the idea is worth it! Python is great at creating prototypes to test ideas, concepts, and products. Python makes it easy to run the analyzing process which helps in building prototypes.
- Job Security
Many career paths which were once thought to be difficult have been made easy with the use of coding and algorithms. If you learn Python for data science, then you can get better career options which might raise a sense of stability and security in the job. Even if you are still in a dilemma about pursuing data science or not, Python is going to have your back as this programming language is accepted in every type of industry!
So, therefore a candidate must learn Python while doing data science courses. By opting for the courses, the candidates will learn to tackle complex issues and get real-world experience. They will also master the tools and technologies of data science in Python.
So, what are you waiting for? Take up these courses and sharpen your skills with data science certification courses.