Why learn Statistics and Python to Become a Data Scientist?

3D illustration of science fiction robot with glowing computer display face

If you like statistics and Python, you can take the right courses to become a data scientist. The data covers many machines, such as cars, robots and smartphones, just to name a few. The amount of data produced by these units requires the use of special tools and procedures for decision-making and analysis. Let’s find out why it is important to learn statistics and Python to become a data scientist. Read on to know more.

In schools, colleges and universities, Python is gaining popularity as a mainstream programming language. The reason is that this language is agile with many libraries and other support materials such as game development and network automation. The good thing is that the Python ecosystem has spawned many libraries to enable data analysis. Therefore, it is part of the data science courses.

Data science life cycle: First, data science has a life cycle that is used for analytics around the world. The purpose of the life cycle is to provide a means to develop hypotheses and then test them.

Python helps you run basic statistical analyzes on a given data set. And these analyzes can include measures of hypothesis testing, probability distribution, and central tendency.

Python also helps you learn more about variables and I/O operations through another example program. Furthermore, the program shows how to enumerate various variables and data types. The beautiful thing about this language is that it has no case statements.

Although not used in data science, object-based design and analysis are also introduced. The purpose of this planning and analysis is to organize the programs around the given modules.

In terms of libraries, courses can include TensorFlow, keras, scikit-learn, Scipy, and Numpy, to name a few. These libraries form the basis of data science using Python.

If you need more information, you can check out Data Science Central, which is a great platform. On this site you can choose from a large number of e-books to learn more about the subject. They also have a forum section to help you participate in discussions. It can further improve your knowledge. Apart from this, many YouTube channels are dedicated to the same purpose. You can take a look at them.

The good news is that many libraries have online sandboxes. They allow you to test the functions of the library. You can follow the tutorials to get started with coding. All you need to do is check out various Python modules for more information. Over time you will learn more.

So this is why Python is so important in the field of data science. If you want to become a data scientist, we suggest you take the appropriate courses to improve your skills in this programming language called Python. I hope this article will be useful for you.

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