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Python Programming for Beginners in Data Science

Data science is all about making sense from different data types and exploring, problem-solving, and getting useful information from different data sets. When it comes to data science, there is no better alternative for Python programming language.  Python data science is becoming a trend in the current IT world, and many professionals are looking to learn Python and enter into the field of data science. In this post, let us understand how one can learn Python and become a good data scientist. 

Reasons to learn Python for Data Science.

Python is one of the most loved programming languages in the IT industry. The large and passionate community backs it. It has a loyal following in the data science profession too. The reason why it is preferred over other programming languages is plenty. Many people determine the quality, performance, and simplicity of the programming languages with the ‘hello world’ program. Python carries out this function pretty well. Simplicity is one of the great strengths of Python, along with other benefits. It can perform the same tasks with lesser code when compared with others. It makes implementing the process quick and efficient. 

The biggest strength of Python is a strong and passionate community. It also has a vibrant data science community, which means you can find plenty of free resources, code snippets, tutorials, and experienced people to solve your problems and questions. The libraries are another notable thing of Python. It makes the data analytics job more accurate and faster. It comes with a separate package for machine learning and data analysis. 

These things make data science programs efficient, accurate, and easy to use. However, one big factor compels many people to jump into the data science space with Python as a programming language. That is the demand. The data generated from every business is reaching an all-time high, and it is expected to grow exceptionally in the next few years. Hence, it is the best time to invest time and money in learning data science with the right programming language. The demand is growing more, and talented professionals can earn lucrative pay. 

How can you learn Python efficiently and quickly?

Before understanding the best practices to learn Python for data science, it is important to know what things are not necessary. You don’t need a degree in C.S to start your learning path as long as you are good at writing logical codes using R or Python. Python is a comprehensive thing and data science is a part of it, so by learning a small part, you can master data science with Python. Besides, you no need to memorize the syntax, rather you can learn to become initiative while writing code.

Learn the fundamentals 

Knowing the basics is the first step in mastering any of the topics. If you know how it works and the core concepts of Python, you can easily relate the logic behind every syntax and your programming becomes a smooth process. Spend your time understanding the core concepts of Python. You can refer to numerous resources to learn the fundamentals of Python. You can find a useful resource online as well as in the books. 

Know the uses of libraries

Python has a large collection of libraries to execute numerous things. When it comes to data science, there are a huge set of libraries to work with. Libraries are the bundles of preloaded objects and functions that can be used in your program to save time rather than programming from scratch.  The essential libraries are NumPy, Matplotlib, Pandas, Seaborn and Scikit-learn. The knowledge of these libraries makes your job easier and help to understand the working of Python in a better way. 

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