What you'll learn

Gain the skills to independently write real world programs in python.
Learn to perform various batch operations.
Brief overview of data science.
Colab notebook environment.
Designing of Reusable Object-Oriented Python Classes.
Vocabulary related to python.
Object attributes and methods.

Requirements

Aspiration to learn python for data science.

Description

This course introduces Python 3 required to get hands on advance libraries (TensorFlow, Numpy, Matplot and Pandas etc.) of data science in python, including conditional execution and iteration as control structures, and strings and lists as data structures.

You'll learn to program python codes in a free cloud based Notebook powered by Google called Colab.

If you are serious about learning data science, you'll require high processing speed to train models with huge data sets, And this course will teach you how to leverage advantages of free GPU (Graphical processing unit) and TPU (Tensor processing unit) provided to you by Google.

The course is for you if you're a newcomer to Python programming, if you need a refresher on Python basics, or if you may have had some exposure to Python programming but want a more in-depth exposition and vocabulary for describing and reasoning about programs and built a strong python foundation for data science environment.

Who this course is for:

Beginner Python developers curious about data science.
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