First, start with the basics of Python such as oops concepts, data types, control statements, functions, multithreading, and exception handling. After getting familiar with the fundamentals, learn using the Numpy library for mathematical computing and pandas library for handling tabular datasets. Also, learn using scikit-learn library and frameworks like Tensorflow or Pytorch for building machine learning and deep learning models. Then, get familiar with the libraries like matplotlib, seaborn, plot.ly libraries for data visualization.
If you want to take a course that can provide Instructor-led training and certification then sign up for this Python for Data Science Certification by Intellipaat.
You can watch this video to know how to learn Python for Data Science:
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