
In this lecture, we will learn about, what are variables, how to define a variable in python, distinguish between invalid/valid variable names, some arithmetic operations using Variables.
In this lecture, we will learn about type of data. We will also learn about different data types that exists in python. Will have a short discussion on each data type, which will be discussed in details in upcoming lectures. In this lecture, we will also learn about how to find the data type of a variable and how to change the data type.
In this lecture, we will learn about how to take an input from user, how to store it and how to use it.
We will also see about different ways of formatting the print statement.
From python point of view, this is very important lecture.
As in this lecture, we will learn about indentation that needs to be maintained while writing loops, if else statements, functions etc.
A complete guide to begin your python learning for data science, data analysis and machine learning.
For those, who has never written a single code in entire life and want to move into data science or advanced python, this course provides you a simple approach to learn coding from scratch using python as a tool and master it with illustrations and assignments.
For those, who are already experienced in coding, but want to move into advanced python, this course provides you ample hands-on exercises and assignments for deeply understanding the concept.
In this course, you will be learning from the very basics - which includes basic numbers, arithmetic operations, lists, sets, tuples, dictionaries, loops, if else statements, nested dictionaries, functions, recursive functions etc.
We will be using Jupyter notebook in order to execute all the codes. Jupyter notebook is a tool that is being used by all the multinational organisation, who hire people for analytics and machine learning jobs.
Key features:
# Learn Python from scratch - from installation to writing your first code to understand the basics and finally to reach advance level.
# No prior coding experience required.
# Command yourself in Jupyter Notebook.
# Prepare yourself for Data Analytics, Machine Learning, Python Development.
Have a great learning ahead.