How To Learn Python for Data Science?

Data science is one of the best career options in this century. To get started with data science, you need to learn linear algebra, math, statistics, and most importantly a programming language. Python is one of the best programming languages for data science because of its readability and beginner-friendly syntax. A lot of beginners often get confused about how to learn Python for data science as there are so many libraries. So which ones you need to learn and how much Python you need to learn for data science? So in this article, I will take you through how to learn Python for Data Science.

What is Data Science?

Data Science is a combination of computer science and data mining. You must have seen a lot of products that works according to your lifestyle and habits. Those products use your data to make your life easier, for example, you must have noticed that you get to see video recommendations according to your interests on YouTube, this is a very useful feature as it saves a lot of time. Data Science is used in making data products.

The process of data science starts with the collection of data, after collecting data we analyze it to find patterns and relationship between the features of data. Then we select the most related features according to the problem we are trying to solve with data and then we use those features to make further decisions or to create a machine learning model.

To understand and analyze the data you have to think like a statistician, and to make decisions based on the patterns in the dataset you have to think like an analyst and to make data products you have to think like a programmer. This is what Data Science is.

Aman Kharwal

How To Learn Python for Data Science?

In data science, we have to implement statistics and mathematics on data by using a programming language. As stated in the beginning, Python is one of the best programming languages for Data Science. Other than Python, you only need to learn SQL. So how to learn Python for Data Science? To learn Python for data science, first, start by learning the fundamentals of Python and then learn the concept of Data Structures and algorithms using Python.

So after learning the fundamentals of Python and the concepts of Data Structures and algorithms using Python you have to learn some Python libraries that will help you to work with data. Below are all the Python libraries that you need to learn step by step for Data Science:

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Seaborn
  5. Scikit-Learn
  6. TensorFlow
  7. PyTorch

NumPy is used for numerical calculations, Pandas is used for data handling, both matplotlib and seaborn are used for data visualization, Scikit-Learn is used for implementing machine learning algorithms on the data, and both TensorFlow and PyTorch are used for training neural networks.

After learning all the libraries step by step you need to focus on implementing all your understanding by solving data science case studies. Here are some of the case studies that you can solve using Python to start your journey towards data science. I hope you liked this article on how to learn Python for Data Science. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
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